Machine Learning Engineer/Senior Machine Learning Engineer - Devops, AI for Drug Discovery

The Opportunity

At Roche's AI for Drug Discovery (AIDD) group (Prescient Design), we are revolutionizing drug discovery with cutting-edge machine learning techniques. We are seeking a highly motivated and skilled ML Infrastructure DevOps Engineer to join our growing team within Genentech Research and Early Development AI Drug Development (gRED AIDD). This role is crucial for building and maintaining the scalable and robust infrastructure that powers our machine learning initiatives.

What you'll do

• Design, implement, and maintain scalable and reliable ML infrastructure on AWS.
• Automate deployment, monitoring, alerting, and operational tasks using tools like Terraform and Helm.
• Manage and optimize CI/CD pipelines and Git repositories for ML projects, ensuring efficient version control to support collaboration and deployment.
• Collaborate closely with ML engineers and data scientists to understand their infrastructure needs and provide solutions.
• Troubleshoot and resolve infrastructure-related issues in a timely manner.
• Implement and enforce security best practices for ML infrastructure.
• Document infrastructure designs, processes, and operational procedures.
• Contribute to initiatives independently as part of a team, delivering assigned outputs.
• Proactively identify issues and gaps, proposing ideas and suggestions for improvements.

Senior Machine Learning Engineer - DevOps

• Lead the architecture and delivery of significant technical solutions.
• Mentor junior engineers and drive technical alignment and influence across teams.
• Demonstrated ability to lead technical projects from conception to completion and deliver high-quality, scalable, and reliable software.

Who you are

• BS/MS with 2-3 years of industry experience required (Machine Learning Engineer - DevOps).
• BS/MS with 3-5 years of industry experience required (Senior Machine Learning Engineer - DevOps).
• Proven experience in designing, deploying, and managing infrastructure on Amazon Web Services (AWS), including services such as EC2, S3, RDS, EKS, SageMaker, etc.
• Strong proficiency with Git and Git repository management.
• Hands-on experience with Terraform for infrastructure provisioning and management.
• Experience with Helm for deploying and managing applications on Kubernetes.
• Proficiency in scripting languages (e.g., Python, Bash) for automation.
• Excellent problem-solving skills and a strong ability to debug complex issues.
• Strong communication and interpersonal skills to effectively collaborate with cross-functional teams and user-facing interactions.
• Demonstrated ability to take initiative, anticipate needs, and drive projects to completion.
• Ability to thrive in a fast-paced environment and adapt to evolving requirements while adhering to corporate guidelines.
• Ability to write clean code with little syntax/convention feedback.
• Applies software engineering best practices (linting automation, unit testing, documentation, CI/CD).
• Familiarity with modern machine learning methods.
• Knowledge of and experience with high-performance computing, distributed systems, and cloud computing.

Preferred

• Experience with MLOps platforms and tools.
• Familiarity with CI/CD pipelines for ML workflows.
• Knowledge of monitoring and logging tools (e.g., Prometheus, Grafana, ELK stack).