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Fireworks is a Series D AI infrastructure company (valued at $17.5B, backed by NVIDIA, Sequoia, Benchmark, and others) building a platform for specialized intelligence. The platform enables enterprises and AI-native startups to build, train, and serve custom AI models tailored to their data, workflows, and products.
As Product Manager for Training, you will own the roadmap, strategy, and success metrics for Fireworks' model training product—spanning API, UI, and CLI interfaces. This is a hands-on role where you'll work directly with customers running real fine-tuning and training workloads, understand their pain points, and translate those into scalable, self-serve product capabilities.
Key responsibilities include:
- Owning the training product roadmap and defining success metrics
- Engaging directly with AI-native startups and enterprises to understand their training workflows and unblock them when they encounter friction
- Converting bespoke work done by forward-deployed and applied ML teams into productized, self-serve capabilities
- Partnering with product marketing, sales, and field teams on launches, including pricing, packaging, documentation, and customer enablement
You'll need 2–8+ years of product management experience building technical or developer-facing products, with a strong technical background (CS/EE degree, production engineering, or equivalent). Familiarity with the post-training lifecycle is essential: dataset curation, supervised fine-tuning (SFT), LoRA/PEFT, RL-based methods, evaluation, and how these connect to production inference.
Preferred qualifications include personal experience fine-tuning models and shipping them to production, background with ML platforms or MLOps tooling, understanding of GPU economics and training cost/quality tradeoffs, and open-source or developer-community experience. Early startup or founding experience is a plus.
This role offers the opportunity to solve hard problems at the frontier of AI infrastructure, work with bleeding-edge technology, and have direct ownership and impact on how businesses harness AI globally.
