Principal ML Investigator

Foundation Capital

Sunnyvale (CA)

On-site

USD 250,000 - 450,000

Full time

14 days+
Application generator

An application made for this job — a tailored resume and cover letter that speak straight to the posting.

Get past ATS filters

Job summary

Cerebras Systems is expanding its ML team to explore new efforts that align with our core platforms. We are seeking a principal investigator who will partner with ML leaders to define the new program, recruit top researchers, and build a capable team to tackle cutting-edge workloads on Cerebras hardware.

The role will coordinate with Field ML, Applied ML, and Core ML teams, drive research in post-training, dataset optimization, LLM pretraining, sparsity, and domain-specific applications, and

Qualifications

  • PhD in Computer Science or related field.
  • Strong grasp of ML theory in one or more areas listed.
  • Proven experience engineering ML systems for scale or production deployment.
  • Experience leading a team of researchers or engineers.

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

ML research
Team leadership
System engineering
Cross-functional collaboration

Education

PhD in Computer Science or related field

Tools

Triton
Distributed training frameworks
LLMs (GPT, Llama)

Job description

Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.

This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.

Cerebras works with the leading model labs, global enterprises, and cutting-edge 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 that can focus on a new ML effort that can align with existing teams. We are seeking a principal investigator who will partner with our ML leaders to formulate the new effort and to build up the new team and capabilities. This new team would coordinate with our current ML teams: Field ML, which works directly with customers, Applied ML, which builds new ML capabilities and applications for customers, and Core ML, which adapts ML algorithms to find unique capabilities of Cerebras hardware. The new team could take up the same or complementary responsibilities.

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:

  1. Build a breakthrough AI platform beyond the constraints of the GPU.
  2. Publish and open source their cutting-edge AI research.
  3. Work on one of the fastest AI supercomputers in the world.
  4. Enjoy job stability with startup vitality.
  5. Our simple, non-corporate work culture that respects individual beliefs.

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

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.

This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.

Get your free, confidential resume review.

or drag and drop your file here.

Similar jobs

Similar jobs worth comparing

Principal ML Investigator
Principal ML Investigator

Cerebras Systems • Sunnyvale (CA)

On-site
USD 180,000 - 240,000
Advanced Technology: AI/ML Research Scientist
Advanced Technology: AI/ML Research Scientist

Cerebras Systems, Inc. • Sunnyvale (CA)

On-site
USD 120,000 - 160,000
Senior Research Engineer - Inference ML
Senior Research Engineer - Inference ML

Foundation Capital • United States

Hybrid
USD 150,000 - 190,000
0
ML Algorithm Mapping and Performance Engineer, Core ML
ML Algorithm Mapping and Performance Engineer, Core ML

Cerebras Systems • Sunnyvale (CA)

On-site
USD 180,000 - 240,000
Principal Engineer, Inference Cloud
Principal Engineer, Inference Cloud

Cerebras • Sunnyvale (CA)

On-site
USD 260,000 - 350,000
ML Software Tool Development Engineer
ML Software Tool Development Engineer

Foundation Capital • United States

On-site
USD 120,000 - 160,000
Equal opportunity employer
Non-corporate work culture
Continuous learning opportunities
Applied Machine Learning Research Scientist
Applied Machine Learning Research Scientist

Foundation Capital • United States

On-site
USD 120,000 - 160,000
Equal opportunity employer
Inclusive work environment
Continuous learning and growth opportunities
ML Systems Integration Engineer
ML Systems Integration Engineer

Cerebras • Sunnyvale (CA)

On-site
USD 140,000 - 190,000
ML Runtime and Kernel Engineer - Core ML
ML Runtime and Kernel Engineer - Core ML

Cerebras Systems • Sunnyvale (CA)

On-site
USD 150,000 - 210,000
Applied ML Research Scientist: Build Scalable LLM Pipelines
Applied ML Research Scientist: Build Scalable LLM Pipelines

Foundation Capital • United States

On-site
USD 120,000 - 160,000
Equal opportunity employer
Inclusive work environment
Continuous learning and growth opportunities