Product Manager, Inference Platform

Location: San Francisco; New York Workplace: Hybrid ABOUT BASETEN 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 https://www.baseten.co/blog/announcing-our-series-f/, led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE Product at Baseten is a nascent function. Our company today has a strong engineering culture, is heavily customer-obsessed, and moves fast. We're building the product function now, and you'd be one of the people who defines it. 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. This space is still evolving. Think cloud infrastructure in the mid-2000s. Your job is to make it 10x easier to reliably scale and serve AI models in production, and to set the market standard. This role is a great fit if you love getting deep in the technical details, and if you'd rather do whatever it takes to ship for customers than stay in the strategy, UX, or docs layer. You're drawn to platforms, systems, GPUs, models, and scaling infrastructure more than to applied AI, and you find real satisfaction in the foundational, sometimes unglamorous work that makes AI systems reliable and scalable at the infrastructure level. EXAMPLE INITIATIVES Take a look at these blog posts written by members of our Product and Infrastructure teams: - How we built Multi-cloud Capacity Management (MCM) https://www.baseten.co/blog/how-we-built-multi-cloud-capacity-management/ - How the Baseten Delivery Network (BDN) makes cold starts fast https://www.baseten.co/blog/how-the-baseten-delivery-network-bdn-makes-cold-starts-fast/ - Baseten brings AI video to life on Nebius https://www.baseten.co/blog/ai-video-nebius-baseten-inference-stack/ RESPONSIBILITIES - 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. REQUIREMENTS - 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. NICE TO HAVE - Hands-on experience with GPU infrastructure. - Experience with Kubernetes. - Experience with serving frameworks like vLLM, TensorRT-LLM, or SGLang. BENEFITS - Competitive compensation, including meaningful equity - (U.S. only) 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 - (U.S. only) Company-facilitated 401(k) - Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities. Apply now to embark on a rewarding journey in shaping the future of AI! If you are a motivated individual with a passion for machine learning and a desire to be part of a collaborative and forward-thinking team, we would love to hear from you. At Baseten, we are committed to fostering a diverse and inclusive workplace. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status. We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance, where applicable).