Staff ML Infra Engineer — Scale, Serve & Optimize Models

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

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.