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Cybersecurity Research Assistant

(ID: 2026-1702)

 

Axle is a bioscience and information technology company that offers advancements in translational research, biomedical informatics, and data science applications to research centers and healthcare organizations nationally and abroad. With experts in biomedical science, software engineering, and program management, we focus on developing and applying research tools and techniques to empower decision-making and accelerate research discoveries. We work with some of the top research organizations and facilities in the country including multiple institutes at the National Institutes of Health (NIH).

 

Benefits We Offer:

  • 100% Medical, Dental & Vision Coverage for Employees
  • Paid Time Off and Paid Holidays
  • 401K match up to 5%
  • Educational Benefits for Career Growth
  • Employee Referral Bonus
  • Flexible Spending Accounts:
    • Healthcare (FSA)
    • Parking Reimbursement Account (PRK)
    • Dependent Care Assistant Program (DCAP)
    • Transportation Reimbursement Account (TRN)

Axle is seeking a Cybersecurity Research Assistant to join our vibrant team supporting rare disease research at the National Institutes of Health (NIH). This is a Remote position within the United States. 

Overview 

Axle supports AI research systems that run on on-premises Kubernetes clusters and shared high-performance computing infrastructure. This role implements and monitors defined security controls across that environment, and helps develop AI tooling that assists with developing and maintaining cybersecurity controls. 

This is a hands-on early-career role for someone with a systems or IT background who wants to move into security engineering. You would be jointly supervised by our AI technical lead and by a lead systems administrator, giving you a direct line into both the security engineering side and the day-to-day operation of the infrastructure you are securing. We are looking for a self-motivated person who wants to build a career in cybersecurity, gaining hands-on experience and earning the certifications that go with it. Axle will sponsor the right candidate for those certifications and provides working hours to study for them. 

Responsibilities 

  • Implement assigned security controls as configuration changes across our Kubernetes, Linux, database, and model-serving environments, working from the control catalog and an assigned task list. 

  • Build out and operate monitoring and detection coverage, including metrics collection, dashboards, log aggregation, and alert routing. 

  • Run vulnerability scanning across container images, hosts, and application dependencies on a set schedule, track findings to closure, and keep the plan of action and milestones current. 

  • Write and maintain the automation that applies hardening baselines and checks them for drift, using Ansible and Python. 

  • Contribute to secrets management, network policy, and role-based access control work across the cluster environments. 

  • Build the deterministic collectors that gather control evidence, including cluster API queries, policy engine reports, scan output, access control dumps, and database configuration exports, normalized into a common format and stored with timestamps. 

  • Help build the internal AI tooling that assists with this work, including retrieval over the control catalog and system documentation, drafting from collected evidence, and triaging scanner output into ranked findings for human review. 

  • Keep security documentation in agreement with the deployed configuration, and raise discrepancies promptly through your supervisors. 

  • Test what you build. Restore a backup and confirm it works, break a policy on purpose and confirm the alert fires, and verify that a control you implemented does what the catalog says it does. 

  • Document what you did in enough detail that an assessor can follow it a year from now. 

  • Prepare material for security reviews and continuous monitoring reports, working with your supervisors on anything that goes to an assessor or an authorizing official. 

Must Have 

  • One to three years of professional experience in IT, systems administration, help desk, network operations, or a comparable hands-on technical role. 

  • Comfort on the Linux command line. You can read a log, trace a permissions problem, and work out what a service is doing. 

  • Scripting ability in Bash and Python. You do not need to be a software engineer, but you should have automated something real and be able to walk us through it. 

  • Demonstrated interest in security. Coursework, a home lab, capture the flag competitions, a Security+ in progress, a personal project, or security work inside a broader IT role all count. 

  • Careful, methodical work habits. Much of this job is doing a procedure correctly, recording what happened, and noticing when the result does not match what was expected. 

  • Willingness to ask questions early and to say plainly when you do not know something. 

  • Ability to work independently on assigned tasks and to give regular updates on what is planned, in progress, and finished. 

  • Ability to obtain and maintain a Public Trust Security clearance. 

Requirements 

  • Associate’s or Bachelor’s degree in Computer Science, Information Technology, Cybersecurity, Information Systems, or a related field. We will consider equivalent professional experience or a completed technical certification program in place of a degree. 

  • Working knowledge of Linux system administration, ideally on RHEL based systems such as Rocky Linux, and on Ubuntu. 

  • Basic understanding of networking, including TCP/IP, DNS, TLS, firewalls, and how a request travels from a browser to a service. 

  • Basic familiarity with containers, and real interest in learning Kubernetes. We will teach it. You should want to learn it. 

  • Familiarity with version control and comfort working in a shared Git repository. 

  • Ability to follow a written procedure precisely, and to notice when the procedure itself is wrong. 

  • Clear written communication. A large part of this role is documenting what was done and why. 

  • Interest in learning how federal security authorization actually works, including NIST security controls, continuous monitoring, and how evidence is assembled and reviewed. 

Desired Skills & Experience 

  • CompTIA Security+, Network+, or Linux+, a Kubernetes certification, or a cloud certification. 

  • Coursework or a degree concentration in cybersecurity or information assurance. 

  • Any exposure to NIST security standards, security frameworks, or compliance work, including academic exposure. 

  • A home lab, capture the flag participation, open-source contributions, or a personal project you can walk us through. 

  • Experience with Ansible, Terraform, or another configuration management tool. 

  • Any experience with Prometheus, Grafana, Elastic, or another monitoring or logging platform. 

  • Curiosity about large language models and about building tools with them. Prior AI experience is not expected. You would learn that here. 

  • Prior work at NIH or another federal agency, or familiarity with federal IT environments. 

Training and Certification 

This is a training role and we mean it literally. You would work alongside experienced engineers on a real federal authorization effort, with two supervisors invested in bringing you up to speed. Axle pays for certification exams and study materials, and this role includes scheduled working hours for study rather than expecting it on your own time. 

The expected path is CompTIA Security+ first, then a Linux or Kubernetes credential such as RHCSA or the Certified Kubernetes Administrator, then Kubernetes security through the Certified Kubernetes Security Specialist. Candidates who want to go further toward the authorization side can pursue CGRC. We will build the specific plan with you based on what you already have. 

What we need from you is the willingness to do careful work and to build a real skill set over the next two years, rather than to arrive with it. 

 

Disclaimer: The above description is meant to illustrate the general nature of work and level of effort being performed by individuals assigned to this position or job description. This is not restricted as a complete list of all skills, responsibilities, duties, and/or assignments required. Individuals may be required to perform duties outside of their position, job description or responsibilities as needed.

The diversity of Axle’s employees is a tremendous asset. We are firmly committed to providing equal opportunity in all aspects of employment and will not tolerate any illegal discrimination or harassment based on age, race, gender, religion, national origin, disability, marital status, covered veteran status, sexual orientation, status with respect to public assistance, and other characteristics protected under state, federal, or local law and to deter those who aid, abet, or induce discrimination or coerce others to discriminate.

Accessibility: If you need an accommodation as part of the employment process please contact: careers@axleinfo.com

This role has a market-competitive salary with an anticipated base compensation range listed below. Actual salaries will vary depending on a candidate’s experience, qualifications, skills, and location.

Salary Range
$85,000—$110,000 USD

Senior Data Scientist, AI Retrieval Systems

Axle is a bioscience and information technology company that offers advancements in translational research, biomedical informatics, and data science applications to research centers and healthcare organizations nationally and abroad. With experts in biomedical science, software engineering, and program management, we focus on developing and applying research tools and techniques to empower decision-making and accelerate research discoveries. We work with some of the top research organizations and facilities in the country including multiple institutes at the National Institutes of Health (NIH).

 

Benefits We Offer:

  • 100% Medical, Dental & Vision Coverage for Employees
  • Paid Time Off and Paid Holidays
  • 401K match up to 5%
  • Educational Benefits for Career Growth
  • Employee Referral Bonus
  • Flexible Spending Accounts:
    • Healthcare (FSA)
    • Parking Reimbursement Account (PRK)
    • Dependent Care Assistant Program (DCAP)
    • Transportation Reimbursement Account (TRN)

 

Axle is seeking a Senior Data Scientist, AI Retrieval Systems to join our vibrant team supporting rare disease research at the National Institutes of Health (NIH). This is a Remote position within the United States. 

 

Position Summary:

Roughly 25 to 30 million people in the United States live with a rare disease. There are somewhere between 7,000 and 10,000 distinct rare conditions, and the large majority have no FDA-approved treatment.

Research on these conditions keeps running into the same obstacles. Published evidence for any one disease is thin and scattered across sources. The same clinical finding gets written down a dozen different ways depending on who recorded it. And the people with the most at stake, patients and their families, are usually the least equipped to read the specialist literature written about their own condition.

Large language models are well suited to this class of problem, and the research programs we support are investing in applying them carefully. In this role you will build the retrieval and knowledge layer that those AI systems stand on. That means the disease and phenotype vocabularies that give a model something precise to reason over, the semantic search that finds the right concept behind an imprecise human phrase, and the ranking that decides what a user sees first. Ontologies serve as internal scaffolding throughout. Users should never have to see one or learn what it is.

This is a senior individual contributor position with unusual range. You will own the data layer, the retrieval services built on top of it, the interfaces where results become visible, and the path onto the computing infrastructure that runs it all. You will work directly with NIH program staff, clinical geneticists, and rare disease information specialists.

 

Core Responsibilities:

  • Model biomedical knowledge for rare disease research. Ingest disease and phenotype ontologies and controlled vocabularies into PostgreSQL with a maintainable release and refresh path, reconcile identifiers across sources, and work through term hierarchies to determine what is clinically relevant for a given condition.
  • Build retrieval-augmented services that ground everyday language in clinical concepts. Embed term labels, definitions, and synonyms, retrieve candidates, and have a model disambiguate against context before any value is committed.
  • Treat retrieval as a database problem. Tune keyword and vector search over large biomedical corpora, and be ready to defend the recall and latency trade-offs you choose.
  • Build the ranking and relevance layers that decide what surfaces first, including domain-aware weighting and graceful degradation when a condition falls outside curated coverage.
  • Deliver the interfaces where this work becomes visible to users, in Next.js, React, and TypeScript. This covers question and confirmation flows, result presentation, and live status for long-running pipelines.
  • Deploy continuously onto NIH on-premises and high-performance computing Kubernetes environments. Helm charts, StatefulSets, secrets, ingress, GPU scheduling for self-hosted inference, and scheduled jobs are all in scope, and you will partner with the operations teams that run those environments instead of standing up parallel cloud infrastructure.
  • Build the evaluation that tells us whether retrieval and concept mapping are good enough to rely on, and keep it running as a regression suite instead of a one-time measurement.
  • Log what the system does and why. Request identifiers, latency, errors, and which concept the system selected all need to be captured, so that staff can review an AI-assisted result instead of taking it on faith.
  • Work out what researchers, clinicians, and patient communities need, and turn it into data models, retrieval behavior, and interface design.
  • Write the work up. You will contribute to manuscripts, conference abstracts, and posters with NIH investigators, and you will be credited as an author on work you helped produce.

 

Required Qualifications:

  • Bachelor’s degree in Data Science, Computer Science, Bioinformatics, Biomedical Informatics, or a related field. An advanced degree is preferred. We will consider equivalent professional experience in place of a degree.
  • At least 5 years building and operating production software or data systems. At least 2 of those years should involve shipping LLM-powered applications (agents, retrieval, or evaluation) that people depend on. We weigh depth in retrieval and applied LLM engineering more heavily than total years.
  • Experience building retrieval systems end to end, covering indexing, query construction, and measuring retrieval quality against real data.
  • Experience evaluating systems that have no single right answer, using golden sets, offline regression suites, or metrics such as Recall@K and MRR to decide whether a change was an improvement.
  • Experience with structured output and tool or function calling, meaning you have constrained a model to a typed schema and validated what came back.
  • Ability to own a service end to end, from schema design through deployment and operation.
  • Ability to obtain and maintain a Public Trust Security clearance.

 

Technical Skills:

  • Python, with FastAPI, Pydantic, and pytest.
  • PostgreSQL at depth, covering vector search (pgvector or equivalent), full-text search, embedding pipelines, indexing, and query tuning.
  • LLM application engineering: provider APIs and gateways, prompt and context design, structured generation, and tool use.
  • Data ingestion and transformation pipelines with a repeatable refresh path.
  • Containers and Kubernetes, enough to ship, debug, and operate a service on infrastructure you do not administer.
  • Working comfort in Next.js, React, and TypeScript.
  • Git-based collaboration and CI/CD in a shared codebase.

 

Preferred Skills:

  • Biomedical ontologies and controlled vocabularies, including MONDO, HPO, UMLS, MeSH, and other OBO Foundry resources, along with comfort working through term hierarchies, synonyms, and cross references.
  • Grounding model output in a domain terminology through embedding-based retrieval plus model disambiguation, such as entity linking, concept normalization, or ontology alignment.
  • Helm, and deployment to on-premises or HPC Kubernetes environments.
  • Serving open-weight models in production with Ollama or vLLM behind a gateway such as LiteLLM, and work with domain embedding models such as MedCPT.
  • Background in rare disease, clinical genetics, or translational research.
  • Contributions to an open biomedical resource, standard, or consortium, such as OBO Foundry ontologies or GA4GH.’
  • Published or presented work that explains your engineering to people who did not build it. Peer-reviewed papers, conference talks, preprints, technical blog posts, and public open source contributions all count.
  • Prior or current NIH experience.

 

We are looking for an engineer first. If you have shipped retrieval systems that people depend on and have never opened an ontology file, we want to hear from you. Rare disease and ontology background is useful but not required, and we expect to teach the domain to whoever we hire. Candidates who meet the required qualifications and none of the preferred ones are encouraged to apply.

 

Disclaimer: The above description is meant to illustrate the general nature of work and level of effort being performed by individuals assigned to this position or job description. This is not restricted as a complete list of all skills, responsibilities, duties, and/or assignments required. Individuals may be required to perform duties outside of their position, job description or responsibilities as needed.

The diversity of Axle’s employees is a tremendous asset. We are firmly committed to providing equal opportunity in all aspects of employment and will not tolerate any illegal discrimination or harassment based on age, race, gender, religion, national origin, disability, marital status, covered veteran status, sexual orientation, status with respect to public assistance, and other characteristics protected under state, federal, or local law and to deter those who aid, abet, or induce discrimination or coerce others to discriminate.

Accessibility: If you need an accommodation as part of the employment process please contact: careers@axleinfo.com

This role has a market-competitive salary with an anticipated base compensation range listed below. Actual salaries will vary depending on a candidate’s experience, qualifications, skills, and location.

 

Salary Range
$130,000—$150,000 USD

Senior Data Scientist, Agentic AI Systems

 
(ID: 2026-3432)
 
Axle is a bioscience and information technology company that offers advancements in translational research, biomedical informatics, and data science applications to research centers and healthcare organizations nationally and abroad. With experts in biomedical science, software engineering, and program management, we focus on developing and applying research tools and techniques to empower decision-making and accelerate research discoveries. We work with some of the top research organizations and facilities in the country including multiple institutes at the National Institutes of Health (NIH).

Benefits We Offer:

  • 100% Medical, Dental & Vision Coverage for Employees
  • Paid Time Off and Paid Holidays
  • 401K match up to 5%
  • Educational Benefits for Career Growth
  • Employee Referral Bonus
  • Flexible Spending Accounts:
    • Healthcare (FSA)
    • Parking Reimbursement Account (PRK)
    • Dependent Care Assistant Program (DCAP)
    • Transportation Reimbursement Account (TRN)

Axle is seeking a Senior Data Scientist, Agentic AI Systems to join our vibrant team supporting rare disease research at the National Institutes of Health (NIH). This is a Remote position within the United States. 

Position Summary 

Roughly 25 to 30 million people in the United States live with a rare disease. There are somewhere between 7,000 and 10,000 distinct rare conditions, and the large majority have no FDA-approved treatment. 

Research on these conditions keeps running into the same obstacles. Published evidence for any one disease is thin and scattered across sources. The same clinical finding gets written down a dozen different ways depending on who recorded it. And the people with the most at stake, patients and their families, are usually the least equipped to read the specialist literature written about their own condition. 

Large language models are well suited to this class of problem, and the research programs we support are investing in applying them carefully. In this role you will build the conversational AI systems that sit between a person and the research infrastructure. These are multi-turn workflows that ask sensible follow-up questions in plain language, capture the answers as validated structured data, and hand that structure off to the searches and analyses doing the scientific work. The emphasis is on systems people can rely on, which in practice means confirming every interpretation before it is saved and logging every automated decision so that it can be reviewed later. 

This is a senior individual contributor position. You will own major components from design through deployment, work directly with NIH program staff, clinical geneticists, and rare disease information specialists, and help set the engineering standards for how AI gets applied on this team. 

Core Responsibilities 

  • Build agentic AI systems for rare disease research workflows. This includes the conversation logic, the rules that decide when enough information has been gathered, and the confirmation steps that catch a misreading before it reaches anything downstream. 
  • Model outputs in Pydantic and use structured output and tool calling, so that every field a model produces is typed, validated, and traceable back to its source. 
  • Write, version, and regression test the prompts behind clinical and scientific reasoning tasks. Prompts and output schemas are treated as code here, with tests to match. 
  • Build evaluation for tasks that have no single right answer. Golden sets, offline regression suites, and model-based graders all have a place, and the results should be good enough to decide what ships. 
  • Keep multi-step LLM workflows responsive under load. This covers async design, concurrency limits, streaming partial results to the client, and timeout and failure handling that holds up in production. 
  • Log what the system does and why. Request identifiers, latency, errors, and the reasoning behind each automated choice all need to be captured, so that staff can review an AI-assisted result instead of taking it on faith. 
  • Work out what researchers, clinicians, and patient communities need, and turn it into data models and system behavior. 
  • Write the work up. You will contribute to manuscripts, conference abstracts, and posters with NIH investigators, and you will be credited as an author on work you helped produce. 

Required Qualifications 

  • Bachelor’s degree in Data Science, Computer Science, Bioinformatics, Biomedical Informatics, or a related field. An advanced degree is preferred. We will consider equivalent professional experience in place of a degree. 
  • At least 5 years building and operating production software or data systems. At least 2 of those years should involve shipping LLM-powered applications (agents, retrieval, or evaluation) that people depend on. We weigh depth in agentic workflow engineering more heavily than total years. 
  • Experience with structured output and tool or function calling, meaning you have constrained a model to a typed schema and validated what came back. 
  • Experience evaluating systems that have no single right answer, using golden sets, offline regression suites, or model-based graders to decide whether a change was an improvement. 
  • Ability to own a service end to end, from schema design through deployment and operation. 
  • Ability to obtain and maintain a Public Trust Security clearance. 

Technical Skills 

  • Python, with FastAPI, Pydantic, and pytest. 
  • LLM application engineering: provider APIs and gateways, prompt and context design, structured generation, tool use, and tracing. 
  • PostgreSQL, including work with embeddings or vector search alongside relational data. 
  • Asynchronous and concurrent Python, plus streaming results to a client. 
  • Containers and Kubernetes, enough to ship, debug, and operate a service on infrastructure you do not administer. 
  • Git-based collaboration and CI/CD in a shared codebase. 

Preferred Skills 

  • A typed agent framework such as Pydantic AI, LangGraph, or the OpenAI or Anthropic agent SDKs, and MCP for tool integration. 
  • LLM tracing and evaluation tooling such as Langfuse, LangSmith, Arize Phoenix, or Braintrust. 
  • Serving open-weight models in production with Ollama or vLLM behind a gateway such as LiteLLM. 
  • Biomedical ontologies and controlled vocabularies, including MONDO, HPO, UMLS, MeSH, and other OBO Foundry resources, along with comfort working through term hierarchies, synonyms, and cross references. 
  • Background in rare disease, clinical genetics, or translational research. 
  • Experience working alongside clinicians, curators, or patient advocacy organizations, and translating their vocabulary into a data model that holds up. 
  • Published or presented work that explains your engineering to people who did not build it. Peer-reviewed papers, conference talks, preprints, technical blog posts, and public open source contributions all count. 
  • Prior or current NIH experience. 

We are looking for an engineer first. If you have shipped LLM systems that people depend on and have never opened an ontology file, we want to hear from you. Rare disease and ontology background is useful but not required, and we expect to teach the domain to whoever we hire. Candidates who meet the required qualifications and none of the preferred ones are encouraged to apply. 

 

Disclaimer: The above description is meant to illustrate the general nature of work and level of effort being performed by individuals assigned to this position or job description. This is not restricted as a complete list of all skills, responsibilities, duties, and/or assignments required. Individuals may be required to perform duties outside of their position, job description or responsibilities as needed.

The diversity of Axle’s employees is a tremendous asset. We are firmly committed to providing equal opportunity in all aspects of employment and will not tolerate any illegal discrimination or harassment based on age, race, gender, religion, national origin, disability, marital status, covered veteran status, sexual orientation, status with respect to public assistance, and other characteristics protected under state, federal, or local law and to deter those who aid, abet, or induce discrimination or coerce others to discriminate.

Accessibility: If you need an accommodation as part of the employment process please contact: careers@axleinfo.com

This role has a market-competitive salary with an anticipated base compensation range listed below. Actual salaries will vary depending on a candidate’s experience, qualifications, skills, and location.

Salary Range
$130,000—$150,000 USD

Associate Director of Data and Modeling

(ID: 2026-3404)

Axle Informatics is a bioscience and information technology company committed to accelerating biomedical discovery through data science, software engineering, scientific computing, and research technology. We work alongside scientists and federal health partners to solve complex technical problems, create durable research infrastructure, and make advanced computational methods more accessible to the people who can use them to advance science.

We believe the best technical organizations combine curiosity with discipline. They make room for experimentation, but they also finish what they start. They build systems that others can understand and sustain. They share knowledge, invest in people, and measure success by what their work enables the research community to accomplish.

If building that kind of organization, and helping it solve some of the most difficult data and computational challenges in biomedical research, excites you as much as it excites us, we would love to talk.

Benefits We Offer:

  • 100% Medical, Dental & Vision Coverage for Employees
  • Paid Time Off and Paid Holidays
  • 401K match up to 5%
  • Educational Benefits for Career Growth
  • Employee Referral Bonus
  • Flexible Spending Accounts:
    • Healthcare (FSA)
    • Parking Reimbursement Account (PRK)
    • Dependent Care Assistant Program (DCAP)
    • Transportation Reimbursement Account (TRN)

Position Overview

Axle Informatics is excited to open the search for an Associate Director of Data and Modeling to help shape the next generation of data-intensive biomedical research. This role will lead teams working across data engineering, artificial intelligence and machine learning, scientific computing, and modeling and simulation to build capabilities that make complex research data more useful, reproducible, and actionable.

The goals this position fills are ambitious; turn difficult scientific and technical problems into durable systems, create the conditions for highly technical teams to do their best work, and ensure that promising ideas become reliable capabilities that researchers can trust.

This is not a role for someone who has only advised technical teams from a distance. The Associate Director must bring the judgment that comes from having personally designed, built, deployed, and operated complex data, software, AI/ML, or scientific computing systems. You will be expected to engage deeply enough to recognize weak assumptions, ask the questions that change a design, help teams resolve difficult technical tradeoffs, and know when an experimental approach is ready to become part of a production environment.

At the same time, the role is larger than any single architecture, model, or platform. You will build and lead multidisciplinary teams, establish shared technical standards, develop emerging leaders, strengthen the operating systems that make delivery predictable, and create reusable approaches that can serve multiple research programs. You will work closely with scientists, engineers, program leaders, security and privacy teams, and federal health partners to connect technical excellence with meaningful scientific outcomes.

Our vision is a future where data, models, simulations, workflows, and analytical tools can be used together with less friction and greater confidence. We value scientific rigor, technical craftsmanship, reproducibility, openness, and service to the research community. If those values energize you, we would love to meet you.

Key Responsibilities: Summary

  • Technical Strategy and Stewardship: Set the technical direction for data platforms, AI/ML systems, scientific computing environments, and modeling capabilities. Establish reference architectures and reusable implementation patterns that help teams make sound decisions while preserving room for experimentation. Decide when to build, modernize, adopt, or partner, and make those decisions with long-term sustainability in mind.

  • Production Data Platforms: Guide the design and operation of data systems that can ingest, transform, harmonize, and serve large, heterogeneous scientific and health datasets. Build repeatable approaches for data quality, validation, terminology translation, lineage, versioning, documentation, and change control so that data products remain understandable and trustworthy as programs evolve.

  • AI/ML and Emerging Methods: Lead the development of AI/ML capabilities where they can create measurable scientific or operational value, including predictive modeling, computer vision, natural language processing, large language models, retrieval-augmented generation, and agentic workflows. Require thoughtful evaluation, traceability, privacy safeguards, human review where appropriate, and monitoring that continues after deployment.

  • Modeling, Simulation, and Scientific Computing: Build a sustainable modeling and simulation practice that supports both specialized scientific work and reusable organizational capability. Establish standards for reproducible workflows, versioned inputs and environments, compute strategy, and scientific validation. Partner effectively with domain experts when the deepest subject matter expertise resides outside your own discipline.

  • From Research to Reliable Systems: Help teams cross the difficult gap between promising prototypes and dependable production capabilities. Strengthen engineering practices around testing, CI/CD, containerization, observability, release management, incident response, documentation, and technical debt. Preserve the creativity of research environments while introducing the discipline required for systems that others depend on.

  • Technical Organization Leadership: Build and lead multidisciplinary teams spanning software engineering, data engineering, machine learning engineering, data science, and computational science. Create clear roles, strong technical leadership paths, and expectations that reward both rigor and collaboration. Develop managers and technical leads who can make good decisions without creating single points of failure.

  • Program Execution and Quality: Create an operating cadence that makes complex technical delivery visible and predictable. Establish clear priorities, risk checkpoints, release criteria, ownership, and measures of progress. Help teams sequence work thoughtfully, address technical debt without losing momentum, and communicate tradeoffs before they become surprises.

  • Governance, Security, and Responsible Use: Work with security, privacy, governance, and scientific stakeholders to ensure that data and AI capabilities are appropriate for sensitive and highly governed environments. Promote practical controls for access, auditability, intended use, model review, data minimization, privacy, and responsible AI without allowing governance to become disconnected from how systems are actually built and used.

  • Open Science and Community Engagement: Encourage technical publication, conference participation, open-source contribution, and active engagement with the broader research software community. Support continued stewardship of reusable scientific platforms and tools, including Polus, and look for opportunities where open collaboration can increase impact beyond a single project or client.

  • Technical Growth and Partnership: Contribute to selected federal growth and proposal efforts as a senior technical leader. Shape credible solution architectures, technical approaches, staffing models, and implementation strategies. Help Axle pursue work that matches its technical strengths and can be executed with the same standards expected of its active programs.

Required Qualifications

  • Eight or more years of progressively responsible experience in software engineering, data engineering, machine learning engineering, computational science, data science, or a closely related technical discipline.

  • Five or more years of leadership experience building and guiding multidisciplinary technical teams, including responsibility for hiring, technical direction, delivery, and staff development.

  • Demonstrated experience personally designing, building, deploying, and operating production-grade data, AI/ML, software, or scientific computing systems.

  • Strong technical judgment across modern data and AI architectures, distributed processing, containerized environments, CI/CD, MLOps or LLMOps, observability, and production operations.

  • Demonstrated success moving analytical or AI/ML work from research and prototyping into reliable production use, including evaluation, deployment, monitoring, versioning, and ongoing operational ownership.

  • Experience building or leading large and complex data pipelines with attention to interoperability, data quality, lineage, reproducibility, and repeatable transformation.

  • Experience leading modeling, simulation, scientific computing, or computational research work directly or in close partnership with scientific subject matter experts.

  • Ability to review technical designs, identify risk, challenge assumptions, resolve difficult engineering problems, and distinguish promising emerging methods from approaches that are not yet ready for production use.

  • Experience delivering technical systems in research-intensive, regulated, or high-governance environments involving sensitive data, security controls, privacy requirements, or formal technical oversight.

  • Strong communication skills and the ability to move comfortably between detailed technical discussion and clear explanation for scientists, program leaders, executives, and government stakeholders.

Preferred Qualifications

  • Advanced degree in computer science, bioinformatics, computational biology, data science, engineering, applied mathematics, physics, or another quantitative discipline.

  • Prior experience as a software engineer, data engineer, machine learning engineer, computational scientist, or equivalent hands-on technical practitioner before moving into broader leadership.

  • Experience leading organizations of approximately 20 or more engineers, scientists, and technical specialists, including managers or senior technical leads.

  • Experience with biomedical or health data platforms and standards such as OMOP, FHIR, PCORnet, CDISC, or related clinical terminology systems.

  • Experience with high-performance computing, large-scale scientific workflows, workflow orchestration, containerized research environments, or petabyte-scale scientific data.

  • Experience deploying Generative AI capabilities with evaluation, retrieval, traceability, privacy controls, human review, monitoring, and appropriate safeguards.

  • Experience applying AI/ML to scientific imaging, genomics, proteomics, real-world data, clinical data, or other high-dimensional biomedical datasets.

  • Track record of technical publications, conference presentations, open-source contributions, patents, or other recognized technical leadership.

  • Experience working with NIH or other federal health and biomedical research organizations.

  • Experience serving as a technical or solution lead for federal proposals, capture efforts, or strategic partnerships.

 

Disclaimer: The above description is meant to illustrate the general nature of work and level of effort being performed by individuals assigned to this position or job description. This is not restricted as a complete list of all skills, responsibilities, duties, and/or assignments required. Individuals may be required to perform duties outside of their position, job description or responsibilities as needed.

The diversity of Axle’s employees is a tremendous asset. We are firmly committed to providing equal opportunity in all aspects of employment and will not tolerate any illegal discrimination or harassment based on age, race, gender, religion, national origin, disability, marital status, covered veteran status, sexual orientation, status with respect to public assistance, and other characteristics protected under state, federal, or local law and to deter those who aid, abet, or induce discrimination or coerce others to discriminate.

Accessibility: If you need an accommodation as part of the employment process please contact: careers@axleinfo.com

This role has a market-competitive salary with an anticipated base compensation range listed below. Actual salaries will vary depending on a candidate’s experience, qualifications, skills, and location.

Salary Range
$150,000—$190,000 USD

Full Stack Developer

(ID: 2026-3389)

 

Axle is a bioscience and information technology company that offers advancements in translational research, biomedical informatics, and data science applications to research centers and healthcare organizations nationally and abroad. With experts in biomedical science, software engineering, and program management, we focus on developing and applying research tools and techniques to empower decision-making and accelerate research discoveries. We work with some of the top research organizations and facilities in the country including multiple institutes at the National Institutes of Health (NIH).

 

Benefits We Offer:

  • 100% Medical, Dental & Vision Coverage for Employees
  • Paid Time Off and Paid Holidays
  • 401K match up to 5%
  • Educational Benefits for Career Growth
  • Employee Referral Bonus
  • Flexible Spending Accounts:
    • Healthcare (FSA)
    • Parking Reimbursement Account (PRK)
    • Dependent Care Assistant Program (DCAP)
    • Transportation Reimbursement Account (TRN)

Overview: 

At Axle Informatics, we work with a number of different clients across the federal space, including the National Center for Advancing Translational Sciences (NCATS) within the National Institutes of Health (NIH). You will be working with a diverse team of full-stack developers, cloud engineers, and subject matter experts to design and build NCATS Notebooks Hub, a cloud-native solution for managing and enabling data analysis and data exploration through interactive developer environments (IDEs) and custom-built dashboarding and visualization applications. Our pipeline utilizes modern containerization and container orchestration tools in a cloud-based platform. 

Qualifications:

  • Bachelor’s Degree in Computer Science, Data Science, Bioinformatics or other related field (years of work experience will be considered in lieu of degree)

  • 3+ years experience working with TypeScript/JavaScript

  • 3+ years experience as a full-stack developer

  • Experience with the following is preferred:

    • Node.js

    • Angular 19+

    • NoSQL databases (MongoDB)

    • Containers and container orchestration tools (Docker, Kubernetes)

    • DevOps tools (Jenkins, GitHub Actions)

  • Familiarity with VCS such as Git

  • Experience with unit and end-to-end testing frameworks

  • Experience with using and leveraging GenAI technologies (i.e., CursorAI, Cline, Windsurf)

 

Relevant Skills:

 

  • Critical thinking, problem solving, and attention to detail

  • Clear, concise communication

  • Technical writing ability

  • Familiarity working in an Agile environment

  • Attention to detail when building visually appealing and intuitive UI

Responsibilities:

  • Build scalable, reliable, and flexible applications in TypeScript using NodeJS and Angular 9+

  • Design, implement, and/or use RESTful web services

  • Implement modern and responsive UI for the web and variety of devices

  • Participate in agile software development, prototyping, testing, and code reviews with a small team of developers

  • Write robust unit and end-to-end tests

 

Disclaimer: The above description is meant to illustrate the general nature of work and level of effort being performed by individuals assigned to this position or job description. This is not restricted as a complete list of all skills, responsibilities, duties, and/or assignments required. Individuals may be required to perform duties outside of their position, job description or responsibilities as needed.

The diversity of Axle’s employees is a tremendous asset. We are firmly committed to providing equal opportunity in all aspects of employment and will not tolerate any illegal discrimination or harassment based on age, race, gender, religion, national origin, disability, marital status, covered veteran status, sexual orientation, status with respect to public assistance, and other characteristics protected under state, federal, or local law and to deter those who aid, abet, or induce discrimination or coerce others to discriminate.

Accessibility: If you need an accommodation as part of the employment process please contact: careers@axleinfo.com

This role has a market-competitive salary with an anticipated base compensation range listed below. Actual salaries will vary depending on a candidate’s experience, qualifications, skills, and location.

Salary Range
$85,000—$100,000 USD

Data Scientist II

(ID: 2026-2574)

 

Axle is a bioscience and information technology company that offers advancements in translational research, biomedical informatics, and data science applications to research centers and healthcare organizations nationally and abroad. With experts in biomedical science, software engineering, and program management, we focus on developing and applying research tools and techniques to empower decision-making and accelerate research discoveries. We work with some of the top research organizations and facilities in the country including multiple institutes at the National Institutes of Health (NIH).

 

Benefits We Offer:

  • 100% Medical, Dental & Vision Coverage for Employees
  • Paid Time Off and Paid Holidays
  • 401K match up to 5%
  • Educational Benefits for Career Growth
  • Employee Referral Bonus
  • Flexible Spending Accounts:
    • Healthcare (FSA)
    • Parking Reimbursement Account (PRK)
    • Dependent Care Assistant Program (DCAP)
    • Transportation Reimbursement Account (TRN)

 

We are seeking a Data Scientist II to join our vibrant team supporting the National Cancer Institute (NCI) at the NIH in Rockville, MD. This role is embedded within NCI’s Center for Biomedical Informatics and Information Technology (CBIIT), where you will directly advance cancer research by building the computational infrastructure that scientists depend on every day.

You will support the full omics data lifecycle across a broad spectrum of modalities, including bulk RNA-seq, single-cell RNA-seq (scRNA-seq), spatial transcriptomics, Digital Spatial Profiling (DSP), whole genome and exome sequencing (WGS/WES), metagenomics, metabolomics, and proteomics, as well as clinical, imaging, and biospecimen data. A core part of this role involves developing workflows that integrate these modalities to support systems-level biological questions, cross-cohort studies, and NCI CBIIT initiatives.

You will collaborate closely with NCI scientists, bioinformaticians, clinician-researchers, data engineers, software developers, and government stakeholders to ensure analytical infrastructure is FAIR-compliant, containerized, version-controlled, well-documented, and purpose-built for long-term reuse across the research community.

Key Responsibilities

  • Bioinformatics Workflow and Data Pipeline Development: Design, build, and maintain reproducible pipelines for diverse biomedical data types — including genomic, transcriptomic, single-cell, spatial, proteomic, metagenomic, metabolomic, and clinical datasets. Develop reusable transformation logic and curated datasets supporting analytics, dashboards, APIs, notebooks, and downstream research workflows.

  • Multi-Omics Analysis: Support NCI CBIIT labs in their analysis workflows including bulk RNA-seq (QC, DEG, GSEA), single-cell RNA-seq (clustering, UMAP/t-SNE, cell type annotation, DEG), and Digital Spatial Profiling (annotation, QC, normalization, spatial deconvolution, volcano plots, heatmaps).

  • Data Integration and Lifecycle Support: Enable reliable data movement from source systems into structured, analysis-ready formats. Support ingestion, curation, metadata capture, source-to-target mapping, schema management, provenance tracking, and long-term maintainability of data products.

  • Statistical Modeling and Machine Learning: Apply statistical and ML methods — including hypothesis testing, regression, clustering, PCA, UMAP, t-SNE, and classification — to biomedical datasets. Incorporate AI/LLM-based extraction where appropriate, with clear validation and communication to stakeholders.

  • Researcher-Facing Applications and Visualization: Build and support interactive dashboards (Shiny, Streamlit), notebooks, reports, and APIs enabling researchers to explore multi-omics and clinical data. Support figure generation for QC, differential expression, pathway, and spatial analyses.

  • Collaboration: Partner with data scientists, bioinformaticians, researchers, developers, and government stakeholders to translate scientific needs into technical specifications, data models, and reusable workflows that accelerate biomedical research.

Required Qualifications

  • Education & Background: Bachelor’s degree in Data Science, Bioinformatics, Computer Science, Biological Sciences, or a related field (advanced degree preferred), or equivalent experience. Demonstrated experience in a data-intensive role supporting biomedical research or scientific computing.

  • Data Science and Bioinformatics Expertise: Strong proficiency in Python and R for analysis, scripting, and visualization. Hands-on experience with at least two omics data types (e.g., bulk RNA-seq, scRNA-seq, spatial transcriptomics, proteomics, metagenomics, GWAS).

  • Analytical Skills: Solid understanding of statistical modeling, dimensionality reduction, clustering, differential expression, and pathway analysis. Ability to work with structured, semi-structured, and unstructured data across relational and data lake environments.

  • Collaboration & Communication: Strong problem-solving skills with the ability to communicate effectively across technical and non-technical audiences. Able to translate scientific needs into technical solutions and clearly articulate risks, assumptions, and limitations.

  • Domain Alignment: Genuine interest in biomedical and translational research. Ability to quickly learn domain-specific terminology and workflows, with awareness of data governance, privacy, and compliance requirements for clinical and research data.

 

Preferred Qualifications

  • Data Platform Experience: Experience building analytics solutions in platforms such as Snowflake, Databricks, or cloud data warehouses, with integrations across databases, APIs, dashboards, and application environments.

  • Bioinformatics Workflow Tooling: Experience with workflow and reproducibility tools used in Galaxy, Terra, Nextflow/WDL, Snakemake, Singularity, or CWL. Familiarity with the scverse Python ecosystem (Scanpy, Squidpy, SCIMAP, AnnData) and spatial single-cell analysis methods, including PhenoGraph, Louvain/Leiden clustering, UMAP, and Ripley’s L statistic, is a plus.

  • Research and Application Enablement: Experience preparing curated datasets for dashboards, APIs, and web applications. Familiarity with Posit Connect, R/Shiny, Streamlit, Jupyter, or similar platforms is a plus.

  • Cloud, HPC, Storage, and Automation: Experience with AWS (EC2, S3, Lambda), object storage, relational databases, scheduled jobs, API integrations, and secure data movement. Familiarity with HPC environments, SLURM/SGE, or NIH Biowulf is preferred.

  • Biomedical Domain Knowledge: Background in biomedical research, clinical research, or healthcare analytics. Familiarity with standards such as HL7/FHIR, CDISC, or OMOP, and experience with clinical, genomic, or biospecimen data is a plus.

  • Governance and Reproducibility: Experience with metadata management, data lineage, open-source code release, containerized analyses, and secure handling of de-identified or access-controlled research datasets.

  • Training and Scientific Enablement: Experience creating documentation, training materials, or workshops for researchers and non-coder audiences. Ability to support tool adoption and explain workflows and results clearly is strongly preferred.

 

Disclaimer: The above description is meant to illustrate the general nature of work and level of effort being performed by individuals assigned to this position or job description. This is not restricted as a complete list of all skills, responsibilities, duties, and/or assignments required. Individuals may be required to perform duties outside of their position, job description or responsibilities as needed.

The diversity of Axle’s employees is a tremendous asset. We are firmly committed to providing equal opportunity in all aspects of employment and will not tolerate any illegal discrimination or harassment based on age, race, gender, religion, national origin, disability, marital status, covered veteran status, sexual orientation, status with respect to public assistance, and other characteristics protected under state, federal, or local law and to deter those who aid, abet, or induce discrimination or coerce others to discriminate.

Accessibility: If you need an accommodation as part of the employment process please contact: careers@axleinfo.com

This role has a market-competitive salary with an anticipated base compensation range listed below. Actual salaries will vary depending on a candidate’s experience, qualifications, skills, and location.

 

Disclaimer: The above description is meant to illustrate the general nature of work and level of effort being performed by individuals assigned to this position or job description. This is not restricted as a complete list of all skills, responsibilities, duties, and/or assignments required. Individuals may be required to perform duties outside of their position, job description or responsibilities as needed.

The diversity of Axle’s employees is a tremendous asset. We are firmly committed to providing equal opportunity in all aspects of employment and will not tolerate any illegal discrimination or harassment based on age, race, gender, religion, national origin, disability, marital status, covered veteran status, sexual orientation, status with respect to public assistance, and other characteristics protected under state, federal, or local law and to deter those who aid, abet, or induce discrimination or coerce others to discriminate.

Accessibility: If you need an accommodation as part of the employment process please contact: careers@axleinfo.com

This role has a market-competitive salary with an anticipated base compensation range listed below. Actual salaries will vary depending on a candidate’s experience, qualifications, skills, and location.

 

#IND

Salary Range
$130,000—$145,000 USD