Who We Are:

The Association of American Medical Colleges is a not-for-profit association dedicated to transforming health care by supporting the entire spectrum of medical education, medical research, and patient care conducted by our member institutions. We are dedicated to the communities we serve and steadfast in our goal to improve the health of all.

At the AAMC, we are committed to supporting our employees with a comprehensive benefits package designed to promote well-being, professional growth, and work-life balance. Highlights include:

• Remote Work – Fully remote work available for most positions 

• Retirement Savings – Generous 403(b) employer contributions and financial wellness resources, including professional financial advising. 

• Health & Wellness Perks – Fitness and bicycle subsidies, on-site and virtual wellness programs (live yoga, meditation, mental health webinars, flu shot clinics, and more) 

• Support & Family Care – Employer paid Employee Assistance Program (EAP) and back-up care options for children, adults, elders, and even pets 

Additional information can be found on our website.

Why us, why now?

​​The Lead AI/ML Data Engineer is responsible for designing, building, and maintaining the data pipelines and platforms that support artificial intelligence and machine learning initiatives. This role focuses on enabling data scientists and analysts by ensuring high-quality, well-structured, and accessible data for model training, evaluation, and deployment. The AI/ML Data Engineer collaborates with data architects, data scientists, and business stakeholders to operationalize machine learning solutions and integrate them into enterprise systems.​ 

How will you make an impact?

Data Pipeline Development for AI/ML:

• Design and implement scalable data pipelines for feature extraction, model training, and real-time/batch inference. 

• Ensure pipelines are optimized for performance, quality, reliability, and reproducibility.

• Apply coding standards, testing, CI/CD, and monitoring practices to all ML data workflows

ML Platform and Infrastructure Support:

• Develop and maintain infrastructure to support machine learning workflows. 

• Work with cloud services and containerization to enable scalable model deployment.​ 

​​Collaboration with Data Scientists​:

• ​​Partner with data scientists to understand model requirements and translate them into engineering solutions.

• Support experimentation with curated, versioned, and well-governed datasets.​ 

​​Feature Engineering and Data Preparation​ :

• ​​Develop reusable feature pipelines and manage feature stores. ​

• Ensure data used in ML models is accurate, consistent, and reliable.​ 

Cross-Functional Collaboration:

• ​​Work with business stakeholders and analytics teams to integrate ML outputs into enterprise applications and reporting systems. ​

• Serve as a technical resource on AI/ML initiatives.​ 

What will you bring to the role?

Required Qualifications:

• Required: Bachelor’s degree in Compu