Senior ML Platform Architect: Scale & Automation

Cognizant; San Francisco (CA); On-site; USD 140,000 - 155,000; Full time

Benefits offered by this job

Medical Insurance

Dental Insurance

Vision Insurance

Life Insurance

Paid holidays

Paid Time Off

401(k) plan

Disability Insurance

Parental Leave

Employee Stock Purchase Plan

Job summary

Cognizant in San Francisco is seeking a Staff Machine Learning Infrastructure Engineer to architect and lead the technical vision for our ML platform initiatives. You will design scalable infrastructure that enables teams to develop, deploy, and operate ML models at scale.

You will drive end-to-end ML data processing, feature platforms, and serving architectures, while mentoring platform engineers and setting reliability and performance standards across the ML lifecycle.

Qualifications

• 10+ years of software engineering experience with 5+ years focusing on ML infrastructure.
• Deep expertise in distributed systems and data processing at scale.
• Strong background in ML platform development and MLOps practices.
• Experience building production ML infrastructure supporting critical business applications.
• Proven track record of leading complex technical initiatives.

Responsibilities

• Architect end-to-end ML infrastructure spanning data processing, feature management, and model serving.
• Design and lead implementation of next-generation ML platforms that support diverse ML workloads.
• Drive technical excellence in ML infrastructure through standardization and automation.
• Build scalable data processing systems and feature platforms handling massive-scale ML workloads.
• Lead cross-functional initiatives and mentor platform engineers.
• Drive infrastructure decisions that impact the entire ML lifecycle.

Education

Master's degree in Computer Science or related field

Tools

Spark

Beam

TorchServe

TensorFlow Serving

Kubernetes

Spark

Job description

Cognizant in San Francisco is seeking a Staff Machine Learning Infrastructure Engineer to architect and lead the technical vision for our ML platform initiatives. You will design scalable infrastructure that enables teams to develop, deploy, and operate ML models at scale.

You will drive end-to-end ML data processing, feature platforms, and serving architectures, while mentoring platform engineers and setting reliability and performance standards across the ML lifecycle.