Cerebras Systems
AI Engineer, Model Quality and Performance
Headquarters/Sunnyvale Office
Sponsorship not specifiedDetected 68 days ago
GitDockerAgentic AICompliance
About the role
- We want someone whose first instinct is "how do I get an AI agent to do this on a loop."
- You'll sit between engineering, product, and customer-facing teams.
Responsibilities
- Design eval suites with AI agents in the loop. For every model release, curate a thoughtful mix of advanced, basic, long-context, and customer-use-case-specific evals. Use Claude to generate, validate, and prune candidate test cases at speed.
- Build product-quality tooling that synthesizes quality + performance data into a single, easy-to-use view.
- Experience building AI agents.
- Design eval suites with AI agents in the loop.
- A taste for tooling design.
Requirements
- Comfort with Docker, Git, and the standard automation stack
- Experience designing evals for agentic / coding / long-context / multimodal use cases.
- Familiarity with open-source eval frameworks (EvalScope, lm-eval-harness, etc.).
- Experience building AI agents. You ship real systems with Claude (or equivalent) as a force multiplier. You've built things that would have been infeasible solo without AI agents in the loop.
- Strong math/stats background..
- A taste for tooling design. You've shipped something that a non-engineer used without complaining. Bonus if AI helped you ship it.
- Performance-tuning experience on custom silicon, GPUs, or FPGAs.
Nice to have
- You've shipped something that a non-engineer used without complaining.
Skills
- Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups.
Benefits
- Bonus if AI helped you ship it.
Company info
- Build a breakthrough AI platform beyond the constraints of the GPU.
- Publish and open source their cutting-edge AI research.
- Work on one of the fastest AI supercomputers in the world.
- Enjoy job stability with startup vitality.
- Our simple, non-corporate work culture that respects individual beliefs.
- You will define what "good" looks like across the models we serve, building AI-driven systems to measure it at scale, and translating those signals into artifacts our customers and product team actually use.
- Build custom evals for target customers by orchestrating AI agents to mine trajectories from their workloads and synthesize representative eval sets.
- Build automations to forecast and benchmark model performance on Cerebras for our top customers, including modeling how fast customer-specific workloads will run in production.
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This listing is sourced directly from Cerebras Systems's careers page and normalized into a canonical job model.