Senior Inference ML API SDET - Sunnyvale, CA, United States

Originally posted 29 June 2026 by the employer.

The ML API Quality team ensures confidence behind every production release shipped to Cerebras Inference Cloud.

About the role

As a Senior Software Engineer in Test for the ML API features team, you will lead testing strategy and execution for AI/ML models, evaluating accuracy, fairness, and performance at scale. You will serve as a key technical leader in delivering and validating all software and hardware components for Cerebras API Features.

What you'll do

• Architect and own end-to-end test strategies for new features, developing scalable tests, frameworks, and tooling.
• Lead contributions to industry-standard benchmarks and drive adoption of rigorous evaluation methodologies.
• Define and drive automation initiatives to significantly improve internal engineering efficiency and test coverage.
• Make strategic decisions around coverage trade-offs, resource requirements, and risk-based testing priorities.
• Serve as a technical anchor in a highly agile environment, adapting quickly to shifting priorities while maintaining quality standards.
• Mentor and guide junior SDETs on testing methodology, debugging practices, and automation development.

What you'll need

• 5+ years of relevant industry experience in software integration, development, or quality engineering.
• Deep expertise in automation and programming using one or more languages such as Python, C++, or Go.
• Proven experience testing compute, machine learning, networking, or storage systems within large-scale enterprise environments.
• Strong track record of debugging complex issues across distributed, scaled-out deployments.
• Demonstrated ability to lead cross-functional quality initiatives involving product development, product management, customer operations, and field teams.
• Excellent verbal and written communication skills, with experience presenting technical findings to both engineering and leadership audiences.

Nice to have

• Hands-on experience with ML workloads including LLM and/or multimodal training or inference.
• Deep familiarity with hardware architecture, performance optimizations, compilers, and ML frameworks.
• Experience designing test strategies for distributed systems, cloud infrastructure, and security validation.
• Experience with microservices deployment, debugging, and orchestration at scale.
• Prior experience owning or significantly contributing to a team's quality engineering culture or test infrastructure.

Skills: testing strategy, test frameworks, ML API features, distributed, scaled-out deployments, automation initiatives