Principal Product Manager

San Jose · USD 190,000-230,000 · 3+ years experience · Full-time · Posted Oct 15, 2026

At a glance

SambaNova is looking for a technical product manager to own the company's model and capability roadmap end to end.
The role serves as the product owner and subject-matter expert on models, turning deep technical understanding into decisions, commitments, and launches.
This is a hands-on product role where you will test new models, find where they shine, and build quick mock-ups showcasing the competitive edge fast inference unlocks.

Own the unified, weighted stack rank of candidate models across customer demand, capability, market adoption, recency, strategic value, and engineering effort.
Own the plan of models × hardware generation × configuration × performance targets, grounded in measured platform data.
Turn priorities into dated commitments with engineering, track them to delivery, and run model launches with Marketing, Docs, and GTM.
Keep the model roadmap and dashboard current as the source of truth for execs, account teams, and customers.
Own the definition of a fully featured model across speed, efficiency, model infrastructure, cloud, and API features.
Find capability and conformance gaps from testing and telemetry, set their priority, and drive them to closure with engineering.
Work with QA and Solutions to set acceptance criteria and the evals a model must pass before it launches.
Run new models through real prompts, agentic tasks, and feature checks to learn what works well, what does not, and where gaps exist.
Build quick demos, prototypes, and product mock-ups that make a model's value concrete for leadership, GTM, and customers.
Track the open-weight model landscape and form a clear view on what matters and why.

Bachelor's degree or higher in Computer Science, Engineering, Machine Learning, or a related technical field.
7+ years of combined experience in product management and technical roles (ML engineering, solutions engineering, research).
3+ years as a PM on AI/ML, developer, or infrastructure products.
Strong working knowledge of LLMs: transformer and MoE architectures, inference trade-offs, and features such as function calling, structured output, and reasoning.
A track record of owning a roadmap and shipping: setting priorities under constraints, saying no with data, and driving cross-functional teams to launch.
Comfort with data: building and maintaining prioritization models, dashboards, and scorecards, and hands-on enough to query an API or change a Python script.
Hands-on with models: comfortable calling model APIs, running evals and quick experiments, and building simple prototypes or mock-ups.
Excellent written and verbal communication, with the ability to present a roadmap and defend trade-offs to executives, engineers, and customers.

Product experience at an inference provider, model lab, AI cloud, or AI hardware company.
Hands-on familiarity with inference stacks (vLLM, SGLang, TensorRT-LLM) and OpenAI/Anthropic-compatible APIs.
Experience designing evals and benchmark methodology for model quality and feature conformance.
A background as an ML or solutions engineer before moving into product.
Experience with enterprise, sovereign AI, or public-sector customers.
An active presence in the open-source model community.

Base salary range of $190,000—$230,000 USD plus equity
95% premium coverage for employee medical insurance
77% premium coverage for dependents
Health Savings Account (HSA) with employer contribution
Dental, Vision, Short/Long term Disability, Basic Life, Voluntary Life, and AD&D insurance plans
Flexible Spending Account (FSA) options including Health Care, Limited Purpose, and Dependent Care
Full subscription to Headspace
Gympass+ membership with access to physical gyms
One Medical membership
Counseling services with an Employee Assistance Program