Sr. Engineer, Machine Learning Operations

Position Overview

The Sr. Engineer, Machine Learning Operations, with minimal guidance, works independently and with cross-functional partners—including biostatisticians, bioinformatics scientists, AI scientists, and software engineers—to deploy, operate, and scale machine learning solutions in production for advanced cancer screening and precision oncology applications.

Essential Duties

• 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.

Minimum Qualifications

• 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.

Preferred Qualifications

• 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.

Pay

Salary Range: National Ranges: $ 123,000.00 - $209,000.00 California Ranges: $152,000.00- $228,000.00 The annual base salary shown is a national range for this position on a full-time basis and may differ by hiring location. In addition, this position is bonus eligible.

Benefits

We are proud to offer an employee experience that includes paid time off (including days for vacation, holidays, volunteering, and personal time), paid leave for parents and caregivers, a retirement savings plan, wellness support, and health benefits including medical, prescription drug, dental, and vision coverage.