Product Manager

Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F, led by Altimeter Capital, Conviction Partners, and Spark Capital.

Product at Baseten is a nascent function. You'll work directly with our founders and with some of the best systems and AI engineers, and you'll set the standard for what product looks like here. PMs at Baseten don't sit above engineers. You earn ownership by being technical, finding the truth in front of customers, building great cross-functional relationships, and shipping great product experiences. Once a model is deployed, keeping it fast, reliable, and economical at scale is where production inference is won or lost. You'll own the surface that makes that happen: how deployments autoscale, how traffic is routed, how the system fails over, and how workloads scale across clusters and regions. You'll own these as products end to end, both how they work under the hood and how customers configure and observe them, and you'll set the roadmap that infrastructure and product teams alike can build toward.

• Own how workloads scale and where they land, from autoscaling to demand (up under load, down to zero when idle) to a single placement policy that expresses region, compliance regime, and capacity preference.
• Give compliance-bound workloads right-of-way on sensitive capacity.
• Make production inference reliable by default, so every request reaches a healthy replica and rolling deploys never drop traffic.
• Define region-aware routing, with multi-region and active-active failover as first-class policy, plus health-aware recovery from stuck or bad replicas.
• Build the release engine beneath safe rollouts: the traffic-shifting that powers canary, shadow, and A/B, along with warm-ups, drain, and probes.
• Push the cost and performance frontier for serving AI at scale across latency, throughput, uptime, and cost efficiency.
• Drive a measurable decline in MTTR through self-serve incident management.
• Set the roadmap that infrastructure and product teams build toward, and own each capability end to end, from backend behavior through the customer-facing configuration and observability surface.

• 8+ years in product management, including deep experience with infrastructure, distributed systems, or ML serving.
• Fluency reasoning about scaling, routing, failover, and the cost/performance frontier, at a level that earns the respect of staff engineers.
• Experience owning capabilities end to end, backend through UX, rather than a single slice.
• Track record driving cross-team roadmaps and the dependencies beneath them.
• Comfort defining a category that doesn't fully exist yet.

• Hands-on experience with GPU infrastructure.
• Experience with Kubernetes.
• Experience with serving frameworks like vLLM, TensorRT-LLM, or SGLang.

• Competitive compensation, including meaningful equity.
• 100% coverage of medical, dental, and vision insurance for employee and dependents.
• Flexible PTO policy including company wide Winter Break (our offices are closed from Christmas Eve to New Year's Day!).
• Paid parental leave.
• Fertility and family-building stipend through Carrot.
• Company-facilitated 401(k).
• Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities.