Remote ML Research Engineer (Part-Time)

VitalSyncLabs; Madison, Northern (WI, KY); Hybrid; USD 55,000 - 96,000; Part time

Job summary

VitalSyncLabs in Madison, Wisconsin, is seeking an ML Research Engineer for a hands-on role combining research with implementation. This part-time, remote-within-US position focuses on developing models and systems that understand health context, including language understanding, information extraction, and evaluating uncertainty.

You’ll compare prompts and retrieval methods, investigate failures, and collaborate with software and medical-evaluation contributors to improve quality, performance,

Qualifications

• Strong Python skills and familiarity with modern ML frameworks.
• Understanding of experimental design, model evaluation, data quality, and leakage prevention.
• Ability to turn an open-ended question into a testable hypothesis and explain results.

Responsibilities

• Implement and evaluate model workflows that interpret information and preserve uncertainty.
• Compare models, prompts, retrieval methods, and processing approaches against evaluation cases.
• Investigate failures involving missing information, conflicting evidence, or unsupported conclusions.
• Explore fine-tuning or training approaches with approved data.
• Collaborate with software and medical-evaluation contributors to improve quality, runtime performance, and release readiness.
• Conduct reproducible experimentation and evaluation workflows, including dataset versioning and regression tests.

Skills

Python

Experiment design

Model evaluation

Research-to-production

Documentation

Tools

Git

PyTorch

TensorFlow

Job description

VitalSyncLabs in Madison, Wisconsin, is seeking an ML Research Engineer for a hands-on role combining research with implementation. This part-time, remote-within-US position focuses on developing models and systems that understand health context, including language understanding, information extraction, and evaluating uncertainty.

You’ll compare prompts and retrieval methods, investigate failures, and collaborate with software and medical-evaluation contributors to improve quality, performance,