Senior Product Manager, AI Models

About the role

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.

Own the Future of AI Inference

Cerebras powers the world's fastest AI inference. As the Product Manager for AI Models, you'll lead the strategic model portfolio that defines our product - deciding which models ship, how they perform, and how the world discovers them.

You'll partner directly with leading AI labs, drive launches that shape the industry, and ensure every model on our platform delivers exceptional quality at unprecedented speed.

What You'll Own

Strategic Model Portfolio

• Own the models roadmap: decide which frontier and open-source models we support based on market demand, research trends, and strategic fit
• Establish partnerships with top model labs, for day0 launches
• Build relationships with open-source maintainers to accelerate community model adoption

Product Quality & Customer Success

• Define and enforce quality standards across our model catalog through systematic evaluation frameworks
• Design benchmarks and evaluations that prove our models deliver production-grade performance
• Own the feedback loop: gather customer insights, identify model weaknesses, and drive improvements with engineering
• Enable strategic customers to integrate our inference into their products-removing blockers and optimizing for their specific use cases

Go-to-Market Excellence

• Lead high-impact model launches that generate buzz and adoption
• Create compelling product marketing: demos, benchmarks, tutorials, and documentation that showcase what's possible on Cerebras
• Craft technical content that resonates with developers and decision-makers alike

Technical Decision-Making

• Select and prioritize performance optimizations (quantization, speculative decoding, etc.) based on customer needs and hardware capabilities
• Collaborate with optimization engineers to implement techniques that maximize our speed advantage
• Balance tradeoffs between quality, latency, throughput, and cost

Cross-Functional Leadership

• Orchestrate launches across model enablement, optimization engineering, deployment, sales, and marketing
• Drive alignment in a fast-moving environment where priorities shift based on model releases and customer needs
• Be the voice of the customer to engineering and the voice of product to customers

Skills & Qualifications

What we need to see

• 5+ years of experience as a product manager, currently at or above the level of Senior PM.
• 5+ years of total technical work experience (e.g. SWE, ML researcher, solution engineer).
• Ability to thrive in a fast-paced, dynamic environment. With an entrepreneurial sense of ownership and ability to lead projects.
• Knowledge and passion for the worlds of open-source models and generative AI research.
• Knowledge of the community model ecosystem, including: PyTorch, Hugging Face, vLLM, and SGLang.
• Highly motivated, independent, organized, and an effective communicator.
• Comfortable using Python with the chat completions API, for basic model testing.

Preferred requirements

How to stand out

• Product manager experience at a model training lab or a company that implements open-source models.
• Experience working with customers in a solution engineering role.
• Experience writing technical marketing assets and social media, with a growing portfolio.
• Experience working in a cross-functional organization, and leading projects across multiple teams.
• Experience writing model quality evaluations and system prompt harnesses.
• Experience writing application code in use cases such as code generation or deep research search application.
• Expertise on agentic flows and current LLM model family architectures.
• Understanding of model compilers and optimization.
• Contributor to communities like vLLM, SGLang, PyTorch, or Hugging Face transformers.
• Experience with model optimization or compression methods like quantization.

Location

• Hybrid at our Sunnyvale, California or Toronto, Canada office.
• Remote possible for candidates willing to travel 1-2x per quarter.