Principal Machine Learning Engineer

The Principal Machine Learning Engineer leads the strategic design and development of advanced machine learning models, driving innovation and exploring emerging technologies. This role involves overseeing the entire lifecycle of ML models, ensuring they meet business and regulatory standards, and collaborating with cross‑functional teams to integrate these models into existing systems. The Principal Machine Learning Engineer writes scalable, production‑ready code, ensures models are explainable and robust, and contributes to the company’s machine learning architecture.

• Independently lead the strategic design and development of machine learning models across multiple projects.
• Innovate with different ML algorithms and architectures to optimize performance.
• Push the boundaries of machine learning, exploring emerging technologies for potential integration.
• Oversee the entire lifecycle of machine learning models, from conception to deployment, ensuring they meet business and regulatory standards.
• Use feature engineering to prepare input data for building ML models and improving their accuracy and performance.
• Write efficient, scalable, and production‑ready code for ML models to be scaled and productionalized in partnership with ML Ops Engineers.
• Collaborate with data scientists to transition models from research to production with support from data leads, ML Operations, and Informatics (IX) team.
• Ensure ML models are explainable, fair, and robust.
• Use ML frameworks such as Tensor Flow, PyTorch, or Scikit‑learn.
• Collaborate with data scientists and data science product owners/managers to translate business requirements into ML models.
• Manage risks and dependencies and proactively address any challenges that arise.
• Contribute to the company’s machine learning architecture in partnership with the IX team to support scalable and repeatable model training and deployment.
• Comply with all laws, regulations and policies that govern the conduct of Genentech activities.

• 8 years of experience working in a machine learning engineer role or related experience.
• Bachelor’s or Master’s degree in Computer Science or a related discipline (preferred).
• Expert in machine learning frameworks such as Tensor Flow, PyTorch, and Scikit‑learn, with a proven track record of leading complex ML projects.
• Solid understanding of statistical methods and machine learning algorithms.
• Proficiency with software engineering best practices, including agile development, code reviews, software change management, build processes, and testing.
• Ability to navigate cross‑functional environments with agile‑based approaches for sprint planning, backlog grooming, and timeline tracking.
• Ability to translate complex concepts into simple, easy‑to‑understand content for a non‑technical audience.

• Extensive experience designing and implementing cutting‑edge data architectures and pipelines.
• Recognized expertise in applying machine learning in highly regulated industries, focusing on strategic impact.
• Experience building and optimizing structured and unstructured big data pipelines, architectures, and datasets.
• Excellent communication skills for effective collaboration with cross‑functional teams.
• Experience in healthcare, pharmaceutical, or other highly regulated industries.

South San Francisco, CA. Relocation assistance is not available.

Expected salary range: $231,280–$429,520. Pay is determined by experience, qualifications, geographic location, and other job‑related factors. A discretionary annual bonus may be available based on individual and company performance.

Genentech is an equal‑opportunity employer. We employ, promote, and otherwise treat all employees and applicants on the basis of merit, qualifications, and competence, in compliance with all applicable federal, state, and local laws. If you have a disability and need an accommodation in connection with the online application process, please contact us by completing the Accommodations for Applicants form.