Exact Sciences is dedicated to changing how the world prevents, detects, and guides treatment for cancer. The Sr. Engineer, Machine Learning Operations will work independently and with cross-functional teams to deploy and scale machine learning solutions for cancer screening and precision oncology, ensuring models are production-ready and aligned with the company's mission.
Responsibilities:
- Designs, implements, and maintains end‑to‑end MLOps pipelines for training, validation, deployment, and monitoring of ML and AI models used in cancer screening and precision oncology solutions
- Builds and operates scalable, secure ML infrastructure on cloud and container platforms (e.g., AWS/Azure/GCP, Docker, Kubernetes) to support batch and real‑time inference workloads
- Implements CI/CD workflows for ML (data, model, and code), including automated testing, packaging, and promotion of models across development, staging, and production environments
- Establishes and manages model and data versioning, experiment tracking, and lineage to ensure reproducibility, auditability, and effective model governance
- Develops and maintains monitoring, logging, and alerting for model performance, data quality, drift, and system health, defining and meeting SLOs/SLAs for critical ML services
- Collaborates with data scientists, bioinformatics and biostatistics partners, and software/platform engineering teams to translate experimental workflows into production‑grade services integrated into customer‑facing and internal applications
- Uphold company mission and values through accountability, innovation, integrity, quality, and teamwork
- Support and comply with the company’s Quality Management System policies and procedures
- Maintain regular and reliable attendance
- Ability to act with an inclusion mindset and model these behaviors for the organization
- Ability to work on a mobile device, tablet, or in front of a computer screen and/or perform typing for approximately 90% of a typical working day
- Ability to travel 5% of working time away from work location, may include overnight/weekend travel
Requirements:
- Bachelor's Degree in a field related to essential duties; or Associates Degree and 2 years of relevant experience; or High School Diploma or General Education Degree (GED) and 4 years of relevant experience
- 5 years of relevant job-related experience
- Demonstrated experience with Python, at least one major ML framework (e.g., TensorFlow, PyTorch, scikit‑learn), containerization and orchestration technologies (e.g., Docker, Kubernetes), and a major cloud platform (e.g., AWS, Azure, GCP) supporting ML workloads
- Demonstrated ability to perform the essential duties of the position with or without accommodation
- Applicants must be currently authorized to work in country where work will be performed on a full or part-time basis. We are unable to sponsor or take over sponsorship of employment visas at this time
- 2+ years of life sciences industry experience working with biological data
- 2+ years of industry experience in molecular diagnostics, preferably cancer diagnostics
- Expertise in data mining approaches within healthcare settings generating insight from routinely collected healthcare data
- Scientific understanding of cancer biology
- Strong programming ability in Python and experience with at least one major ML framework (e.g., TensorFlow, PyTorch, scikit-learn)
- Hands-on experience deploying and operating machine learning models in production, including experience with CI/CD pipelines, model packaging, and automated deployment