# Associate Director of Data and Modeling

**Company:** [Axle](https://hotfix.jobs/companies/axle)
**Location:** Remote
**Role:** Data Engineering
**Salary:** $150k – $190k/yr
**Experience:** 8+ years
**Skills:** Data Engineering, Artificial Intelligence, Machine Learning, Scientific Computing, Modeling And Simulation, Python, Data Platforms, LLMs, Natural Language Processing, Computer Vision, CI/CD, Docker, Observability, Data Governance, Responsible Ai
**Posted:** 2026-08-25

> Leads multidisciplinary teams building production-grade data platforms, AI/ML systems, scientific computing environments, and modeling capabilities for biomedical research. The role requires at least eight years of technical experience, five years leading technical teams, and hands-on experience operating complex systems.

## Job Description

## Responsibilities

### Technical Strategy and Stewardship
- Set technical direction for data platforms, AI/ML systems, scientific computing environments, and modeling capabilities.
- Establish reference architectures and reusable implementation patterns.
- Decide when to build, modernize, adopt, or partner with long-term sustainability in mind.

### Production Data Platforms
- Guide the design and operation of systems that ingest, transform, harmonize, and serve large scientific and health datasets.
- Establish repeatable approaches for data quality, validation, terminology translation, lineage, versioning, documentation, and change control.

### AI/ML and Emerging Methods
- Lead AI/ML capabilities including predictive modeling, computer vision, natural language processing, large language models, retrieval-augmented generation, and agentic workflows.
- Require evaluation, traceability, privacy safeguards, human review where appropriate, and post-deployment monitoring.

### Modeling, Simulation, and Scientific Computing
- Build a sustainable modeling and simulation practice.
- Establish standards for reproducible workflows, versioned inputs and environments, compute strategy, and scientific validation.

### From Research to Reliable Systems
- Help teams turn prototypes into dependable production capabilities.
- Strengthen testing, CI/CD, containerization, observability, release management, incident response, documentation, and technical-debt practices.

### Technical Organization Leadership
- Build and lead multidisciplinary teams spanning software engineering, data engineering, machine learning engineering, data science, and computational science.
- Create technical leadership paths and develop managers and technical leads.

### Program Execution and Quality
- Establish priorities, risk checkpoints, release criteria, ownership, and progress measures.
- Sequence work thoughtfully, address technical debt, and communicate tradeoffs.

### Governance, Security, and Responsible Use
- Partner with security, privacy, governance, and scientific stakeholders in sensitive, highly governed environments.
- Promote access controls, auditability, intended-use controls, model review, data minimization, privacy, and responsible AI.

### Open Science and Community Engagement
- Encourage technical publication, conference participation, open-source contribution, and research software community engagement.
- Support stewardship of reusable scientific platforms and tools, including Polus.

### Technical Growth and Partnership
- Contribute as a senior technical leader to federal growth and proposal efforts.
- Shape solution architectures, technical approaches, staffing models, and implementation strategies.

## Requirements

- 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.
- Experience personally designing, building, deploying, and operating complex data, software, AI/ML, or scientific computing systems.
- Experience with technical strategy, production systems, team leadership, delivery practices, governance, security, privacy, and responsible AI.

## Benefits

- 100% medical, dental, and vision coverage for employees.
- Paid time off and paid holidays.
- 401(k) match up to 5%.
- Educational benefits for career growth.
- Employee referral bonus.
- Flexible spending accounts for healthcare, parking, dependent care, and transportation.

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