Principal DevOps Engineer - ML / AI Algorithms

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Principal DevOps Engineer – ML / AI Algorithms

As Principal DevOps Engineer – ML / AI Algorithms, you will work on products that help people with the most precious thing they have – their health. You will be part of the RIS Research & Development team contributing to digital health products touching Imaging, ML / AI, and computational science.

The Opportunity

As Principal DevOps Engineer, you will collaborate with important stakeholders on the development of the build, release, and deploy toolchain for DevOps, paving the way for seamless and efficient software delivery processes.

Locations

This role can be based in Santa Clara (primary location) or in secondary locations (Mississauga, Canada or Basel, Switzerland).

Key responsibilities

Lead the initiative to set up, manage, and meticulously maintain parity across development, staging, and production application environments in cutting‑edge cloud infrastructure, ensuring a robust and consistent deployment pipeline.

Champion the implementation of advanced monitoring infrastructure, empowering the team with real‑time insights and ensuring the highest levels of system reliability and performance.

Provide dedicated on‑call support for production operations, ensuring the uninterrupted delivery of critical services and swift resolution of any operational issues.

Interface with software developers, product managers, test engineers and administrators on projects to design and develop the build, release, and deploy toolchain for DevOps while providing on‑call support.

Identify, troubleshoot and resolve issues quickly and effectively, sometimes under pressure.

Actively involved in planning, high availability engineering, performance tuning, and automation / tools development.

Manage multiple releases with focus on system reliability, scalability, and efficiency.

Implement and manage the full lifecycle of machine learning models, including versioning, deployment strategies (e.g., canary, A / B testing), monitoring for drift and performance, and decommissioning.

Bring in leadership quality to improve technology and process of devops as well as provide mentorship to other devops engineers in the team.

Who You Are

Bachelor's degree in Computer Science, Engineering, or a related field with a minimum of 8+ years of experience in a DevOps or equivalent combination of education and experience to perform at this level.

8+ years of experience with container technology, including Kubernetes, AWS EKS, Helm Charts, Splunk, and Docker, along with provisioning infrastructure through IAC using Terraform and cloud automation principles.

Proficiency in Unix / Linux administration in Shell scripting and internals with a preference for Ubuntu.

Deep working experience and extensive knowledge in building and deploying infrastructure using IaC frameworks such as Terraform and AWS Cloudformation / SAM.

Experience building and automating scalable data pipelines for ingesting, transforming, distributed computing and versioning large-scale image datasets.

Familiarity with DevOps practices and proficiency in log analysis and monitoring tools are essential for effective troubleshooting and system optimization.

Proficiency in Python for automating production systems, including Git, Gitlab, Git actions, GitHub CI / CD, familiarity with common ML libraries such as TensorFlow, PyTorch, and scikit‑learn to understand the engineering needs of the ML models you will be deploying.

Strong working knowledge of AWS Cloud infrastructure, including EC2, S3, API Gateway, Kubernetes, RDS, VPC peering, Route53, IAM, Batch, Lambda, AWS Config and Autoscaling.

Preferred

MLOps experience with demonstrated experience supporting machine learning or computer vision teams.

Deep experience with container orchestration for ML workloads using Kubernetes, including frameworks like Kubeflow or KubeRay to manage distributed training jobs.

Familiarity with data versioning tools like DVC.

Familiarity with common ML libraries such as TensorFlow, PyTorch, and scikit‑learn to understand the engineering needs of the ML models.

Familiarity with other languages such as Java, R, and C / C++.

Experience with AWS services for machine learning, such as Amazon SageMaker, and experience managing GPU‑accelerated compute instances (e.g., EC2 P and G series) for model training and inference.

Compensation

The expected salary range for this position based on the primary location of Santa Clara, CA is between $162,600 and $302,000. Actual pay will be determined based on experience, qualifications, geographic location, and other job‑related factors permitted by law. A discretionary annual bonus may be available based on individual and Company performance. This position also qualifies for the benefits detailed at the link provided below.

Benefits

Relocation benefits are not available for this position.

About Roche

A healthier future drives us to innovate. Together, more than 100,000 employees across the globe are dedicated to advance science, ensuring everyone has access to healthcare today and for generations to come. Our efforts result in more than 26 million people treated with our medicines and over 30 billion tests conducted using our diagnostics products. We empower each other to explore new possibilities, foster creativity, and keep our ambitions high, so we can deliver life‑changing healthcare solutions that make a global impact.

Equal Opportunity

Roche is an equal opportunity employer. It is our policy and practice to employ, promote, and otherwise treat any and all employees and applicants on the basis of merit, qualifications, and competence. The company’s policy prohibits unlawful discrimination, including but not limited to discrimination on the basis of protected veteran status, individuals with disability status, and consistent with all federal, state, or local laws.

If you have a disability and need an accommodation in relation to the online application process, please contact us by completing this form Accommodations for Applicants.

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