Principal Applied Scientist

Cerebras has developed a radically new chip and system to dramatically accelerate deep learning applications. Our system runs training and inference workloads orders of magnitude faster than contemporary machines, fundamentally changing the way ML researchers work and pursue AI innovation.

We are innovating at every level of the stack – from chip, to microcode, to power delivery and cooling, to new algorithms and network architectures at the cutting edge of ML research. Our fully-integrated system delivers unprecedented performance because it is built from the ground up for deep learning workloads.

About the role

The AppliedML team is seeking a senior technical leader to spearhead new initiatives on Generative AI solutions. In this role, you will lead a team of research and software engineers to plan, develop, and deliver end-to-end solutions trained on massive supercomputers. These projects may be part of our customer collaborations or open-source initiatives. These solutions will be trained on some of the largest systems and using some unique datasets we have developed in partnership with our diverse collaborators. You will plan and design experiments, execute them using Cerebras' unique workflow, and share the findings with internal stakeholders and external partners.

Responsibilities

• Lead the technical exploration – from framing the problem statement, defining the option space, and approaching the options in a data-driven way to identify the final approach
• Design experiments to test the different hypotheses analyze output to distill the learnings, and use them to adjust the project direction.
• Keep up with the state-of-the-art in Generative AI – efficient training recipes, model architecture, alignment, and instruction tuning, among others.
• Influence and mentor a distributed team of engineers.
• Integrate and enhance the latest research in model compression, including sparsity and quantization, to achieve super-linear scaling in model performance and accuracy.
• Breakthrough efficiency through co-designing hardware capabilities, model architecture, and training/deployment recipes.

Requirements

• MS in Computer Science, Statistics, or related fields
• Experience with technical leadership of a moderate size team for 2+ years.
• Hands-on experience with training DL models for speech, language, vision, or a combination of them (multi-modal).
• Experience with being the technical lead of a feature or project from conception through productization.
• Experience operating in a self-directed environment with multiple stakeholders.
• Experience working with other leaders to define strategic roadmaps.
• Proven track record of clearly articulating the findings to a broad audience with varying technical familiarity with the subject matter.

Preferred: 

• Ph.D. in Computer Science, Statistics, or related fields.
• Publications in top conferences such as NeurIPS, ICML, and CVPR, among others.
• Track record of building impactful features through open source or productization.
• People management experience is desired.

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

Read our blog: Five Reasons to Join Cerebras in 2024.

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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