Remote Archives

Data Scientist, Medical Imaging

(ID: 2026-3989)

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)

Position Overview

Axle Informatics is seeking a Data Scientist with a strong background in medical imaging and AI to help turn clinical images into research-ready data and models. You will join a team that builds reproducible pipelines for preparing, segmenting, and analyzing medical images, and for linking imaging results to clinical data for machine learning.
This is a hands-on role. You will write and maintain production Python, apply both AI and traditional image analysis methods to large imaging collections, and build and evaluate models that combine imaging with other clinical data. You will be expected to check results critically and catch problems before they become findings. 
The work supports biomedical research programs with federal health partners. You will work in a highly interdisciplinary environment, where progress depends on understanding colleagues from other disciplines and helping them understand you. It values scientific rigor, reproducibility, well-tested code, and open collaboration. If you enjoy the full path from raw images to a validated model, and want that work to be usable by others, we would love to meet you.
Key Responsibilities: 

Medical Image Processing: Build and maintain Python pipelines that prepare large, varied medical imaging collections for analysis, with attention to metadata quality and the inconsistencies found in real clinical data.
AI for Medical Imaging: Develop, apply, and evaluate AI models for segmentation, classification, and image embeddings. Judge model quality and decide when a model needs retraining or a different approach.
Traditional Image Analysis: Apply established image analysis methods for registration, normalization, and feature extraction, and combine them with machine learning where they fit the problem.
Machine Learning and Multimodal Modeling: Build and evaluate models that combine imaging with clinical data and reports, using sound validation practices.
Clinical Data Integration: Work with clinical data models and standard vocabularies to connect imaging results with patient records, cohorts, and outcomes.
Reproducible, Scalable Workflows: Run pipelines with workflow orchestration, containers, and cluster or cloud computing. Keep code tested and documented so others can rerun the work.
Collaboration and Communication: Work closely with clinicians, imaging scientists, and software engineers to define questions and interpret results. Present findings clearly, and contribute to publications, conference presentations, and open-source tools.

 
Required Qualifications
Master’s degree or PhD in biomedical engineering, computer science, data science, medical physics, electrical engineering, or a related quantitative field, or a Bachelor’s degree with equivalent experience.
Three or more years of hands-on experience in medical image analysis, in research or industry.
Strong Python skills, including scientific computing and deep learning libraries, with a habit of writing tested, maintainable code.
Familiarity with DICOM, NIfTI, and other medical image formats.
Experience applying AI to medical images across segmentation, classification, and embeddings.
Experience with traditional image analysis algorithms for registration, feature extraction, and machine learning.
Experience evaluating models rigorously on imaging data, with sound validation design and appropriate performance metrics.
Experience working with clinical imaging data and its privacy requirements.
Comfort working in Linux environments with version control and containers.
Collaboration & Communication: Ability to work effectively in a highly interdisciplinary environment with clinicians, imaging scientists, biologists, and software engineers, and to explain complex technical concepts clearly to people in other disciplines. 
 
Preferred Qualifications
Experience with Nextflow or similar workflow orchestration tools on clusters or cloud platforms.
Experience with EHR data, clinical data models such as OMOP or FHIR, and standa
clinical vocabularies.
Familiarity with the OMOP medical imaging extension, or with imaging data in research data warehouses.
Experience with multimodal models that combine imaging with EHR data or clinical text, including medical foundation models.
Experience with microscopy or digital pathology image analysis.
Experience with SQL and relational or analytical databases.
Track record of publications, conference presentations, or open-source contributions in medical imaging or machine learning.
Experience working with NIH or other federal health and biomedical research organizations.
 

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

$120,000—$130,000 USD

Research Data Manager

(ID: 2026-3882)

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)

Position Overview

The Research Data Manager will build and maintain the data infrastructure for the SOM Center. This includes the Laboratory Information Management System (LIMS), document and repository platforms such as Invenio, and the metadata databases and pipelines that connect them. The role brings together instrument, assay, and analysis data and makes it findable, traceable, and reusable, in line with NIH data management and sharing requirements. The position combines hands-on software development with data stewardship, using cloud-native tooling and AI/ML to make data easier to find and use.

Key Responsibilities

Data integration. Connect laboratory instruments, analysis pipelines, and external data sources to the LIMS. Build and maintain automated ingestion pipelines with validation, logging, and error handling.
Data wrangling and format conversion. Write and maintain custom scripts and services that convert, normalize, and harmonize heterogeneous data formats (instrument exports, imaging metadata, omics outputs, spreadsheets) into standardized schemas.
Repository and document management. Deploy, configure, and support document and research data management systems such as Invenio. Manage records, metadata schemas, persistent identifiers, and access controls.
Database development. Design, create, and maintain databases for experimental metadata and small-to-moderate datasets, including schema design, migrations, indexing, and backup and recovery.
AI/ML-assisted discovery. Incorporate ML/AI into data workflows and user interfaces, such as semantic search, metadata extraction and auto-annotation, and natural-language query tools, to help researchers find and use data.
Platform and cloud engineering. Develop, containerize, and deploy software solutions on cloud or local Kubernetes resources. Maintain CI/CD pipelines, monitoring, and infrastructure-as-code.
Tool evaluation. Evaluate and recommend packages, platforms, and standards for data management, and prepare short technical assessments for IDSS leadership.
Training and documentation. Train laboratory and analytical staff, and write standard operating procedures and technical documentation.

Required Qualifications

Education and experience. Bachelor’s degree in computer science, bioinformatics, data science, or a related field, plus five or more years of relevant experience. A master’s degree may substitute for two years of experience.
Programming and databases. Proficiency in Python, including data libraries (pandas and similar) and API development, plus SQL and experience with relational databases (for example PostgreSQL). Experience with NoSQL or search technologies (for example Elasticsearch/OpenSearch) is a plus.
Data engineering. Experience writing production-quality scripts and services for data conversion, ETL/ELT, and system integration.
Containers and cloud. Hands-on experience with Docker and Kubernetes, and with at least one major cloud platform (AWS, Azure, or GCP).
Software engineering practices. Experience with Git, CI/CD, and practices such as testing and code review.
Research systems. Experience with LIMS, ELN, or comparable research data systems in a biological or biotechnology laboratory setting.
Data standards. Working knowledge of metadata standards, data modeling, and FAIR data principles.
Communication. Strong communication skills and the ability to train and support scientific staff.
Clearance. Ability to obtain and maintain NIH/HHS security clearance and meet federal contractor suitability requirements.

Preferred Qualifications

Experience deploying or customizing Invenio/InvenioRDM or similar repositories (Dataverse, DSpace, CKAN).
Experience integrating ML/AI components into applications, such as embeddings and vector search, LLM-based retrieval, or document parsing.
Familiarity with workflow tools (Airflow, Nextflow, Snakemake, Argo) and with Helm, Terraform, or similar infrastructure-as-code tools.
Experience with stem cell or tissue engineering laboratories.
Experience with imaging and omics data.
Experience with high-performance computing environments (for example NIH Biowulf).
Experience with front-end tooling (React or similar) for data-facing interfaces.

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

Salary Range

$105,000—$150,000 USD

Bioinformatics / Data Scientist

(ID: 2026-3883)

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)

Position Overview

The Bioinformatics / Data Scientist will conduct comprehensive analyses of multi-omics data generated from organoid systems and corresponding normal tissues. The position is central to the SOM Center’s research objectives, focusing on characterizing organoid fidelity, identifying biomarkers of successful differentiation, and developing computational frameworks for organoid quality assessment.

Key Responsibilities

Multi-omics analysis. Analyze complex datasets including single-cell RNA sequencing, bulk RNA sequencing, proteomics, and metabolomics data from a range of organoid systems and their tissue counterparts.
Experimental design consultation: Collaborate with experimental wet-lab on experimental design to better optimize protocols for knowledge discovery and performance.
Pipeline development. Develop and implement computational pipelines for data processing, quality control, and statistical analysis.
Benchmarking. Integrate SOM-generated data with publicly available datasets in order to benchmark organoid characteristics against normal tissue profiles.
Collaboration and interpretation. Work closely with experimental teams to interpret results and guide protocol optimization.
Dissemination. Contribute to manuscript preparation and present findings at scientific conferences.

Required Qualifications

Education. Doctoral degree (PhD) in bioinformatics, computational biology, biostatistics, or a related quantitative field.
Single-cell analysis. Extensive experience with single-cell data analysis, including familiarity with tools such as Seurat, Scanpy, or comparable platforms.
Programming. Strong programming proficiency in R and Python, together with experience in statistical analysis and data visualization.
Omics workflows. Basic knowledge of proteomics and metabolomics data.

Preferred Qualifications

Prior experience analyzing organoid datasets.
Experience with machine learning approaches for biological data, familiarity with pathway analysis tools, and knowledge of developmental biology principles.
Experience with high-performance computing environments and version control systems.

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

#IND

Salary Range

$105,000—$120,000 USD

Bioinformatics Scientist – HIV-SOMAL

(ID: 2026-3884)

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)

Position Overview

The Bioinformatics Scientist will address the bioinformatics, scientific computing, and data analysis needs of investigators within the NIAID Division of Intramural Research (DIR) and their collaborators, as part of the Integrated Data Sciences Section (IDSS) within the Research Technologies Branch (RTB), with particular emphasis on HIV research. The incumbent will provide analysis support across genomic and clinical research data — including viral sequence, host–pathogen, and immunologic datasets generated by HIV studies — develop and maintain production pipelines, and contribute to a scalable resource supporting NIAID scientists. A substantial portion of the work will directly support HIV investigators and their laboratory and clinical research teams. The successful candidate will be highly motivated, adaptable, structured, and detail-oriented.

Key Responsibilities

Scientific consultation. Address the bioinformatics, scientific computing, and data analysis needs of users within the NIAID Division of Intramural Research and their collaborators, providing expertise in the statistical design of biological experiments involving high-throughput genome-scale technologies, data mining and knowledge discovery techniques, automated workflow development, and experimental design consultation.
Bioinformatics support. Provide support spanning somatic and germline variant calling and analysis, single-cell and bulk gene expression analysis, de novo assembly of genomes and transcriptomes, comparative genomics of model and non-model organisms, proteomics, ChIP-seq, and ATAC-seq, including development of high-throughput pipelines for these data modalities.
Programming support. Provide programming and troubleshooting support to the Research Technologies Branch and collaborating Institutes in the dissemination of research data.
Data analysis. Perform computational data analysis on genomic and clinical research data, and provide statistical support and analysis on research data.
Collaboration. Work with staff on scientific programming and experimental design.
Publication. Contribute to and co-author scientific publications in leading peer-reviewed journals.
Resource development. Contribute to the development of a scalable and flexible resource providing next-generation sequencing bioinformatics, structural and computational biology, and machine learning data support to NIAID scientists and investigators.

The Bioinformatics Scientist is expected to bring strong skills in the following areas:

Next-generation sequencing analysis (whole-exome, whole-genome, RNA-seq, ChIP-seq, using both long- and short-read technologies)
Statistical modeling
Scripting
Biological interpretation

Required Qualifications

Clearance. Ability to obtain and maintain a Public Trust security clearance.
Education. Minimum of a bachelor’s degree in a related field; master’s degree or doctorate preferred.
Experience. Four or more years of experience in bioinformatics, including two or more years developing and maintaining production bioinformatics pipelines.
Programming languages. Expert-level proficiency in two of the following: Python, R, C/C++, sh/bash.
Containerization. Experience building images using one of the following: Docker, Podman, Singularity/Apptainer.
Pipeline frameworks. Expert-level proficiency in one pipeline framework: Snakemake, Nextflow, or CWL/WDL.
Documentation. Demonstrated expertise building technical and user documentation for tools, pipelines, and applications.
Infrastructure. Experience building pipelines on-premises using available high-performance computing infrastructure.

Preferred Qualifications

Experience supporting HIV research, including the analysis of HIV sequence data — for example viral genome assembly, phylogenetic and quasi-species analysis, drug-resistance profiling, or characterization of the latent reservoir.
Familiarity with HIV and infectious disease data resources and host–pathogen study designs, including integration of viral sequence data with host genomic, transcriptomic, or immunologic datasets.
Experience building pipelines or applications in the cloud using AWS, GCP, or Azure.
Experience building applications using one of the following frameworks: Django, Flask, RShiny, Electron, Flutter, or React.
Experience working in a laboratory setting.

Please submit a cover letter with your resume that addresses the following questions:

What experience do you have working with large datasets and compute clusters?
Describe your experience of building workflows/pipelines and/or using bioinformatics software and tools to analyze data.
What programing languages are you comfortable using for bioinformatics data analysis?
What are the bioinformatics areas you are familiar with? E.g. Single cell, bulk genomics, transcriptomics, epigenetics, flow, spatial, metagenomics, etc.
What life science disciplines do you have experience in? E.g. Immunology, infectious disease, cancer research, etc.
Provide examples of basic concepts in machine learning/AI and/or applying them in bioinformatics data analysis?
Have you worked with organoid data sets in the past and if so, please explain the experience you have.
Have you worked with HIV data sets in the past and if so, please explain the experience you have.

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

Salary Range

$105,000—$130,000 USD

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

Salary Range

$85,000—$110,000 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

Salary Range

$150,000—$190,000 USD