Research Engineer | Data-Centric AI for Medical Imaging

Alt; San Francisco (CA); On-site; USD 180,000 - 240,000; Full time

Job summary

Epsilon Health is seeking an exceptional Research Engineer or Research Scientist to advance how we curate data and evaluate frontier AI models for medical imaging. You will own the systems that determine data quality and how we measure model performance, building a foundation for clinically accurate AI.

You will work across our research team, collaborating with scientists and engineers developing vision foundation models and post-training methods.

Qualifications

• We care more about what you've built and discovered than where you've worked or how many years you've spent doing it.
• Strong expertise in machine learning, data-centric AI, model evaluation, or research engineering.
• Demonstrated ability to design and build robust data pipelines, evaluation systems, or ML research infrastructure.
• Strong Python programming skills and the ability to develop reliable, scalable research tooling.
• Experience in at least one core area: dataset curation and quality, or evaluation of generative and multimodal models.
• Ability to independently identify research bottlenecks, formulate solutions, and execute projects end to end.
• Strong engineering fundamentals and experience working with complex datasets or ML systems.
• A rigorous, experimental mindset and the ambition to solve difficult, unsolved problems.

Responsibilities

• Build scalable data filtering, curation, and quality pipelines for training datasets across medical imaging modalities.
• Advance data-centric AI research by detecting label noise, image-report misalignment, duplicates and other quality issues.
• Redefine AI evaluation with rigorous frameworks for radiology report generation, focusing on clinical accuracy, completeness, hallucinations, and factual consistency.
• Collaborate with radiologists to translate clinical judgment into data quality and evaluation signals.
• Develop intelligent evaluation systems, model-based evaluators, automated grading methods, and human-in-the-loop workflows.
• Own research infrastructure end to end with benchmarks, evaluation pipelines, and regression testing.
• Drive research across the organization by identifying bottlenecks and developing tools to accelerate the team.
• Share technical insights and contribute to publications or open-source research.

Skills

Machine learning

Data-centric AI

Model evaluation

Research engineering

Python

Data pipelines

Engineering fundamentals

Tools

Spark

Airflow

Job description

Epsilon Health is seeking an exceptional Research Engineer or Research Scientist to advance how we curate data and evaluate frontier AI models for medical imaging. You will own the systems that determine data quality and how we measure model performance, building a foundation for clinically accurate AI.

You will work across our research team, collaborating with scientists and engineers developing vision foundation models and post-training methods.