Staff Machine Learning Infrastructure Engineer

Cognizant; San Francisco (CA); On-site; USD 130,000 - 145,000; Full time

Benefits offered by this job

Health/dental/vision

Paid holidays

401(k) plan

Disability insurance

Parental leave

Employee stock purchase plan

Job summary

Cognizant is seeking a Staff Machine Learning Infrastructure Engineer to architect and advance scalable ML infrastructure for enterprise-scale models. You will collaborate with data scientists, ML engineers, and platform teams to deliver reliable, high-performance ML systems.

The role emphasizes end-to-end ML platforms, scalable infra, and leadership in technical strategy, with an onsite requirement in Sunnyvale, CA.

Qualifications

• 10+ years of software engineering experience, including 5+ years focused on ML 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.

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.

Skills

ML infra

Distributed systems

MLOps

Data pipelines

Model serving

Containerization

Cloud-native

Leadership

Spark/Beam

TorchServe

TF Serving/Triton

Kubernetes

Education

Master’s degree in CS

Tools

Spark

Beam

Feature stores

Kubernetes

Docker

Job description

About the role

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.

In this role, you will:

• 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.

Work model

At Cognizant, we strive to provide flexibility wherever possible, and we are here to support a healthy work-life balance through our various well-being programs. Based on this role’s business requirements, this is an onsite position requiring 5 days per week in a client or Cognizant office in Sunnyvale, CA.

The working arrangements for this role are accurate as of the date of posting. This may change based on the project you’re engaged in, as well as business and client requirements. Rest assured; we will always be clear about role expectations.

What you need to have to be considered

• 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.

These will help you stand out

• 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're excited to meet people who share our mission and can make an impact in a variety of ways. Don't hesitate to apply, even if you only meet the minimum requirements listed. Think about your transferable experiences and unique skills that make you stand out as someone who can bring new and exciting things to this role.

Salary and Other Compensation:

Applications will be accepted until October 04, 2026

The annual salary for this position is between $ 130,000 - $ 145,000 depending on experience and other qualifications of the successful candidate.

This position is also eligible for Cognizant’s discretionary annual incentive program, based on performance and subject to the terms of Cognizant’s applicable plans.

Benefits: Cognizant offers the following benefits for this position, subject to applicable eligibility requirements:

• 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

Disclaimer: The salary, other compensation, and benefits information is accurate as of the date of this posting. Cognizant reserves the right to modify this information at any time, subject to applicable law.