Staff Machine Learning Infrastructure Engineer

About the Position

Staff Machine Learning Infrastructure Engineer

As a Staff Machine Learning Infrastructure Engineer, you will make an impact by architecting and advancing scalable machine learning infrastructure that enables the development, deployment, and operation of ML models at enterprise scale. You will be a valued member of the ML Platform Engineering team and work collaboratively with data scientists, machine learning engineers, platform engineers, and cross-functional technology stakeholders to deliver reliable, high-performance ML systems.

Responsibilities

• Architect and evolve end-to-end machine learning platforms supporting data processing, feature management, training, and model serving.
• Design and implement scalable infrastructure that enables efficient development, deployment, and operation of ML workloads.
• Drive technical strategy, standards, and best practices for machine learning infrastructure, automation, and platform reliability.
• Lead the design of real-time and batch inference solutions that support high-volume production workloads.
• Mentor engineers, lead technical reviews, and partner with data science teams to accelerate ML adoption and innovation across the organization.

Requirements

• 10+ years of software engineering experience, including 5+ years focused on machine learning infrastructure, MLOps, or platform engineering.
• Deep expertise designing and operating distributed systems and large-scale data processing platforms.
• Proven experience building and supporting production ML platforms that power mission-critical business applications.
• Hands-on experience with technologies such as Apache Spark, Apache Beam, feature stores, and large-scale data pipelines.
• Strong knowledge of ML serving and inference platforms, including TorchServe, TensorFlow Serving, Triton, or similar technologies.
• Experience with containerization, orchestration platforms, cloud-native architectures, and infrastructure automation.
• Demonstrated success leading complex technical initiatives and influencing architecture decisions across engineering organizations.

Nice to Have

• Experience designing and optimizing GPU-based infrastructure for machine learning workloads.
• Background in high-performance computing environments.
• Expertise in ML observability, monitoring, reliability engineering, and operational excellence.
• Contributions to open-source machine learning infrastructure, platform engineering, or MLOps projects.
• Master’s degree in computer science, Engineering, or a related technical field.
• Experience supporting security, governance, and compliance requirements within ML ecosystems.

We Offer

• Competitive salary between $130,000 - $145,000 depending on experience and other qualifications of the successful candidate.
• Cognizant’s discretionary annual incentive program, based on performance and subject to the terms of Cognizant’s applicable plans.
• Benefits:
  • Medical/Dental/Vision/Life Insurance
  • Paid holidays plus Paid Time Off
  • 401(k) plan and contributions
  • Long-term/Short-term Disability
  • Paid Parental Leave
  • Employee Stock Purchase Plan

About the Company

Cognizant (Nasdaq: CTSH) is an AI Builder and technology services provider, bridging the gap between AI investment and enterprise value by building full-stack AI solutions for our clients. Our deep industry, process, and engineering expertise enables us to build an organization’s unique context into technology systems that amplify human potential, drive tangible outcomes, and keep global enterprises ahead in a fast-changing world. See how at cognizant.ai or follow us on Twitter.

Additional Information

• Location: Sunnyvale, CA, United States
• Work Model: Onsite (5 days per week)
• Application Deadline: October 04, 2026
• Job Category: Digital
• Employment Type: Full-time
• Experience Level: Senior

Cognizant is an equal opportunity employer. Your application and candidacy will not be considered based on race, color, sex, religion, creed, sexual orientation, gender identity, national origin, disability, genetic information, pregnancy, veteran status, or any other characteristic protected by federal, state, or local laws.

If you have a disability that requires reasonable accommodation to search for a job opening or submit an application, please email [email protected] with your request and contact information.