Product Manager, Inference Platform

Reposted 2 Months Ago
2 Locations
Hybrid
235K-335K Annually
Mid level
Software
Inference will be the largest market ever created.
The Role
As a Core Product Manager, you will shape the developer experience for AI applications, driving the roadmap for APIs, UI, and workflows, while collaborating with design and engineering teams.
Summary Generated by Built In

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, 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)

  • How the Baseten Delivery Network (BDN) makes cold starts fast

  • Baseten brings AI video to life on Nebius

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).

Skills Required

  • 4+ years of Product Management experience in developer tools, SaaS, or ML platforms
  • Degree in Computer Science, Electrical Engineering, or related field; or equivalent hands-on experience as a software engineer
  • Experience driving cross-functional alignment across design, engineering, and GTM teams

Baseten Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Baseten and has not been reviewed or approved by Baseten.

  • Fair & Transparent Compensation — Feedback suggests pay targets the top of market with explicit ranges in postings and a stated aim to provide 90th percentile salaries with equity. Role descriptions emphasize competitive, experience-based pay bands and meaningful stock grants.
  • Healthcare Strength — Healthcare is described as fully covered for medical, dental, and vision for employees and their families, reducing out-of-pocket costs. This comprehensive coverage is consistently highlighted alongside other core benefits.
  • Leave & Time Off Breadth — Time off policies include unlimited PTO with a minimum expectation of at least four weeks, 16 paid company holidays, and a company-wide winter break. These elements indicate substantial protected time away from work.

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The Company
HQ: San Francisco, CA
350 Employees
Year Founded: 2019

What We Do

AI’s future won’t be a few massive models built by a handful of labs. It’ll be millions of specialized models embedded into every product, workflow, and experience by the people closest to the customer. The foundation of that future is inference. Inference determines the performance, reliability, latency, and economics of every AI product. For AI to scale globally, it must be as reliable, fast, cost-effective, and high-quality as possible. That’s why Baseten exists. Companies like Abridge, Cursor, Lovable, Notion, and OpenEvidence depend on Baseten to power mission-critical AI workloads in production.

Why Work With Us

We’re an interdisciplinary team of researchers, engineers, and operators building the Inference Cloud our AI future demands. We’re running at a hard systems problem that requires first-principles thinking across the entire stack. The bar is high. We work hard, move fast, and care deeply about quality.

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