At Exact Sciences, the Senior Engineer, Machine Learning Operations is responsible for deploying, operating, and scaling machine learning solutions that power advanced cancer screening and precision oncology applications. You will design, build, and maintain robust ML platforms and pipelines that ensure reliability, security, and compliance across the full model lifecycle.
What You'll Do
- Design, implement, and maintain end-to-end MLOps pipelines for training, validation, deployment, and monitoring of ML and AI models used in cancer screening and precision oncology solutions.
- Build and operate scalable, secure ML infrastructure on cloud and container platforms (e.g., AWS/Azure/GCP, Docker, Kubernetes) to support batch and real-time inference workloads.
- Implement CI/CD workflows for ML (data, model, and code), including automated testing, packaging, and promotion of models across development, staging, and production environments.
- Establish and manage model and data versioning, experiment tracking, and lineage to ensure reproducibility, auditability, and effective model governance.
- Develop and maintain monitoring, logging, and alerting for model performance, data quality, drift, and system health, defining and meeting SLOs/SLAs for critical ML services.
- Collaborate 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.
- Act with an inclusion mindset and model these behaviors for the organization.
- 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.
- Travel 5% of working time away from work location, which may include overnight/weekend travel.
What We're Looking For
- Bachelor’s Degree in a field related to essential duties; or Associates Degree and 2 years of relevant experience; or High School Diploma or 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.
Nice to Have
- 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.
Technical Stack
- Python, TensorFlow, PyTorch, scikit‑learn
- Docker, Kubernetes
- AWS, Azure, GCP
Team & Environment
You will work with cross‑functional partners including biostatisticians, bioinformatics scientists, AI scientists, and software engineers.
Benefits & Compensation
- Paid time off (including days for vacation, holidays, volunteering, and personal time).
- Paid leave for parents and caregivers.
- Retirement savings plan.
- Wellness support.
- Health benefits including medical, prescription drug, dental, and vision coverage.
- Compensation: National Ranges: $123,000.00 - $209,000.00; California Ranges: $152,000.00 - $228,000.00.
We are an equal employment opportunity employer. All qualified applicants will receive consideration for employment without regard to disability, protected veteran status, and any other status protected by applicable local, state, or federal law.
