AI Enablement ML Engineer for Drug Discovery

Genentech; South San Francisco (CA); On-site; USD 148,000 - 274,000; Full time

Benefits offered by this job

Discretionary bonus

Job summary

Genentech in South San Francisco seeks an experienced machine learning engineer to design, build, and scale AI/ML driven science platforms. You’ll collaborate with computational scientists and product teams to deliver robust web apps and backend systems for data-driven discovery.

You will optimize ML models, evaluate AI quality, and help shape the tech stack while staying current with evolving AI practices. On-site collaboration is essential.

Qualifications

• Strong proficiency with AI/ML frameworks and toolsets.
• Expert knowledge of statistics, ML theory, and algorithms.
• Experience with ML performance optimization and GPU best practices.
• Familiarity with cloud-native architectures (AWS preferred).

Responsibilities

• Design, develop, and test scalable AI/ML facing applications and backend systems.
• Build tools to evaluate AI/ML model performance and understand AI quality.
• Partner with product managers and scientists to translate user needs into specs.
• Develop and maintain systems for collecting, structuring, and storing data for analytics.
• Implement or evaluate new AI/ML algorithms and analytical techniques.
• Contribute to architectural decisions and code reviews.
• Span the stack and adapt to needs beyond core area.
• Stay current with AI tech and promote continuous learning.

Skills

AI/ML frameworks

Statistics

ML theory

GPU optimization

Kubernetes

Relational databases

NoSQL/data lakes

Cloud-native

Communication

Tools

Kubernetes

Job description

Genentech in South San Francisco seeks an experienced machine learning engineer to design, build, and scale AI/ML driven science platforms. You’ll collaborate with computational scientists and product teams to deliver robust web apps and backend systems for data-driven discovery.

You will optimize ML models, evaluate AI quality, and help shape the tech stack while staying current with evolving AI practices. On-site collaboration is essential.