Principal ML Investigator

We would like the new team to work on some of the following areas:

Post-training and reinforcement learning: Techniques used to improve model deployment quality through further training, tuning, RL, and focus on particular downstream tasks;

Dataset curation and optimization: Techniques to collect and select high-quality data, which can help models to train or tune more quickly or to higher quality;

LLM Pretraining: Techniques to ensure stability and compute-efficiency while pretraining high quality models. May include training dynamics, parameterizations, numerics, or others;

Sparsity: Techniques to sparsify models or data that improve training time-to-quality, or optimize inference speed or throughput;

Domains: Coding agents, reasoning agents, generative language, image, video.

Principal Investigator Responsibilities

Build up a team capable of industry research and advanced development.

Organize various advanced development topics into 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 above areas.

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 in training speed optimizations, such as model architecture transformations to target hardware, or low-level kernel development (e.g., Triton).

Ability to analytically model or optimize system performance.

Why Join Cerebras

People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:

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.

Find out more about what it's like to work at Cerebras here!

Apply today and become part of the forefront of groundbreaking advancements in AI!

Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.

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