Principal ML Investigator
Cerebras · Sunnyvale, CA
About this role
## Principal ML Investigator **About Cerebras Systems** Cerebras builds the world’s largest AI chip—an architecture designed to deliver industry-leading training and inference speeds (reported as up to **10x faster** than GPU-based hyperscale cloud inference services). This speed increase is enabling real-time iteration and more agentic computation for smarter AI applications. Cerebras works with leading model labs, global enterprises, and AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras to deploy **750 megawatts** of scale, transforming key workloads with ultra high-speed inference. --- ## About the Role Cerebras is adding an ML team focused on a new ML effort that can align with existing teams. The **Principal Investigator** will partner with ML leaders to define the new effort, build the team and capabilities, and coordinate with current ML groups: - **Field ML**: works directly with customers - **Applied ML**: builds new ML capabilities and applications for customers - **Core ML**: adapts ML algorithms to leverage unique capabilities of Cerebras hardware The new team may take on the same or complementary responsibilities and could focus on one or more of the following areas: - **Post-training & Reinforcement Learning**: improve deployment quality via further training, tuning, RL, and downstream-task focus - **Dataset Curation & Optimization**: collect/select high-quality data to improve training speed and/or final quality - **LLM Pretraining**: ensure stability and compute efficiency while pretraining high-quality models (training dynamics, parameterizations, numerics, etc.) - **Sparsity**: sparsify models or data to improve time-to-quality and/or inference speed/throughput - **Domains**: coding agents, reasoning agents, generative language, image, and video --- ## Principal Investigator Responsibilities - Build up a team capable of industry research and advanced development - Organize advanced development topics into a cohesive agenda - Adapt novel algorithms and model architectures to run on the Cerebras platform - Systematically train, tune, and evaluate models to guide/advise production scenarios - Collaborate with other teams to co-design next-generation hardware and software architectures - Collaborate with external partners (customers, academic) to drive insight and credibility --- ## Skills & Qualifications - **PhD** in Computer Science or related field - Strong grasp of ML theory in one or more of the areas above - Proven experience engineering ML systems for scale or production deployment - Experience leading a team of researchers or engineers --- ## Preferred Skills & Qualifications - Track record of patents or publications in top-tier conferences or journals - Experience with large language models (e.g., GPT family, Llama) - Experience with distributed training concepts and frameworks - Experience with training speed optimizations (e.g., architecture transformations for hardware, low-level kernel development such as Triton) - Ability to analytically model or optimize system performance --- ## Why Join Cerebras Cerebras is building a breakthrough AI platform beyond GPU constraints. With rapid growth and frequent model releases, the company is at an inflection point. **Team highlights (as stated by Cerebras):** 1. Build a breakthrough AI platform beyond GPU constraints 2. Publish and open-source cutting-edge AI research 3. Work on one of the fastest AI supercomputers in t
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