Machine Learning Engineer
New York, Ny, Us
Ezra (www.ezra.com) is a company dedicated to providing early cancer detection for everyone by using the most advanced medical imaging technology. Its ultimate goal is to offer a whole-body MRI scan in a single session and analyse it using the Ezra AI to quickly and accurately screen for precursors to cancer, cancer, and major disease states.• Managed a team of 5 (3 full-stack, 1 MLOps, 1 QA tester). Held weekly 1:1 meetings, conducted performance reviews, interviewed, hired, retained and mentored talent. Led user interviews, collaborated with and communicated technical details with non-technical stakeholders• Architected, built, and deployed a machine-learning solution that converts sophisticated radiology reports to a layman's summary (see BusinessWire article), saving medical staff 75 minutes per report, a 600% productivity boost and a 72.7% cost reduction• Implemented model and API testing suites and added them to our CI/CD pipeline (using DVC, S3, and GitHub Actions), allowing us to build and release with high velocity• Monitored deployed models using CloudWatch, SNS, Sentry, and Slack API• Built and deployed retraining pipelines allowing us to continue to improve the medical staff's efficiency• Built Python RESTful APIs for receiving radiology reports and initiating the ML inference pipeline• Led the engineering team building the non-machine learning components of the product by setting priorities, reviewing code, conducting design meetings, planning release cycles, and sprints• Took the initiative of creating and writing a company tech blog post with an average of 5K views per article, boosting Ezra’s SEO and aiding with recruitment• Member of the Ezra culture committee, helped with organizing in person and virtual events to build organization-wide camaraderie