Level

Baseten

Product Manager, Inference Platform

Baseten is hiring a Product Manager, Inference Platform for a remote role open to applicants in United States. It pays $165k-$330k a year and Level rates it ; you can apply on Baseten.

Level's read on this job

  • On Level's scale, this AI product manager role is Builds AI ●●●●: the job is building AI systems.
  • The posting lists this role as remote.
  • Tools and skills the posting cites include vLLM, Cursor and Clay.
  • Level lists 106 other open roles at Baseten.

AI in this role

vllmcursorclay
ai-research

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:

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).

How we rate this

Product Manager, Inference Platform at Baseten rates 86 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

AI ResearchvLLMCursorClay

Also common in AI product manager jobs at this level

Pay

This job starts at
$165k
Typical AI product manager job
$180k

This posting starts 8% below the typical AI product manager job. See AI product manager jobs

Questions you could be asked

  1. Tell me about a research question you investigated. What did you find?
  2. Walk me through how you've used vLLM in your day-to-day work.
  3. What are the limits of Cursor that you've run into, and how did you work around them?
  4. What's a project where you used Clay hands-on?
  5. How would you decide a model or AI system is ready to ship?

Adapt your resume

  • List these exact terms on your resume: AI Research, vLLM, Cursor, and Clay. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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