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.
• Support and comply with the company’s Quality Management System policies and procedures.

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