Machine Learning Engineer, Infra, AI for Drug Discovery

About the role

At Genentech, we are committed to advancing healthcare through innovation. Our focus on integrating AI and data science into drug discovery is transforming how we develop new therapies. The Computational Sciences Center of Excellence (CoE) is dedicated to maximizing the potential of these technologies, enabling our scientists to deliver groundbreaking medicines.

Key facts

What you'll do

• Develop and maintain scalable infrastructure for machine learning model serving, including scientific and agentic workloads.
• Enhance our internal model deployment platform to ensure it is reliable and user-friendly for teams across the organization.
• Optimize platform performance, focusing on scalability, reliability, and reducing latency.
• Create tools for monitoring model usage, performance metrics, and resource consumption.
• Improve model deployment usability through the development of APIs, command-line tools, and comprehensive documentation.
• Integrate real-time and batch inference workflows on shared platform capabilities.
• Contribute to the infrastructure for model lifecycle management, including registration, versioning, and monitoring.
• Build event-driven systems to streamline model workflows from publication to retraining.
• Collaborate with various teams to translate requirements into effective solutions and eliminate infrastructure challenges.
• Oversee projects from design to implementation, ensuring best practices in software engineering are followed.

Requirements

• Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field, or equivalent experience.
• Minimum of 3 years of relevant experience in software engineering, infrastructure engineering, or a related field.
• Proficient in Python and experienced in developing and deploying production software.
• Hands-on experience with cloud systems, preferably AWS, utilizing services like EKS, EC2, S3, IAM, SQS, and CloudWatch.
• Familiarity with containers, Kubernetes, and infrastructure as code tools such as Terraform or Pulumi.
• Knowledge of CI/CD practices, Git workflows, and automated testing.
• Strong troubleshooting skills for complex systems using observability tools like Datadog or Prometheus.
• Understanding of distributed systems concepts, including concurrency and failure recovery.
• Ability to communicate technical concepts clearly to both technical and non-technical stakeholders.
• Demonstrated capability to deliver practical solutions while balancing immediate and long-term needs.

Nice to have

• Experience with model-serving frameworks such as KServe or Triton.
• Knowledge of optimizing model performance metrics like startup time and throughput.
• Familiarity with MLOps platforms and model evaluation processes.
• Experience in building event-driven architectures.
• Interest in scientific computing and drug discovery processes.

Practical notes

Relocation assistance is not offered for this position.

The anticipated salary range for this role in California is $147,600 to $274,000, and in New York, it is $141,100 to $262,100. Actual compensation will depend on various factors including experience and qualifications. A discretionary annual bonus may be available based on performance. This position is also eligible for benefits as outlined in the provided link.

Genentech is an equal opportunity employer. We are committed to hiring and promoting individuals based on their qualifications and merit, without regard to any protected status. If you require assistance due to a disability during the application process, please reach out through the provided accommodations form.