Machine Learning Engineer

Quick Facts

• Role: Machine Learning Engineer (Computer Vision)

Description

Own the ML pipeline end to end—data, annotation, training, evaluation, deployment, and monitoring—for computer vision models used in the lab. Train and ship PyTorch detection and segmentation models that find and measure tissue, define trustworthy data/labels, and build evaluation to support lab-ready ship / don’t ship decisions. Monitor production failures and feed them back into training while executing work in compliance with the Quality System and Information Security System.

Responsibilities

• Own the computer vision ML pipeline end to end: data, annotation, training, evaluation, deployment, monitoring
• Train and ship tissue detection and segmentation models (PyTorch)
• Decide what data to collect and label; keep datasets and annotation tooling trustworthy
• Build evaluation to predict in-lab performance and enable ship/don’t-ship decisions
• Diagnose production model failures and iterate training based on those failures
• Execute responsibilities in compliance with the Quality System and Information Security System

Requirements

• 5+ years of experience, with models you trained running in production
• Skepticism toward metrics until failure cases are reviewed
• Generalist who can build the tooling and infrastructure ML needs
• Self-starter with a bias toward shipping
• Comfortable making calls under ambiguity; willing to pause and ask when needed
• Direct communication; flags risks early
• Strong opinions, loosely held

Benefits

• Ownership of ML decisions that ship to labs
• Flexible vacation and work schedule
• $170–195k plus equity