Baseten

Technical Program Manager, Model Performance at Baseten (San Francisco, CA)

Baseten· San Francisco, CA· $165k–$330k·

Role details

Salary
$165k–$330k
Work type
Hybrid
Employment
Full-Time
Equity
Yes

Baseten at a glance

AI inference platform for deploying, optimizing, and running machine learning models in production at scale.

Baseten runs trained AI models in production for other companies, handling the GPUs, autoscaling, runtime, and performance tuning so engineering teams get a fast, reliable API without operating the infrastructure themselves. It supports open source, custom, and fine tuned models across managed cloud, hybrid, and self hosted deployments.

$2B+ raised · latest: Series F · $1.5B · June 2026 (valuations of $13B and $11B across two tranches) · backed by Altimeter Capital, Conviction, Spark Capital, Sands Capital

Job description

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 baseten.co/, led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products.

THE ROLE

The Model Performance organization at Baseten is looking to hire our first Technical Program Manager. This is a zero-to-one role in a team that is responsible for building the core algorithms and methods that power Baseten’s high performance inference stack. You won't inherit an existing program framework, you'll build one from the ground up: the planning structure, execution processes, metrics and the cross-functional alignment that a fast-growing organization needs. Your contributions will directly impact how fast our performance R&D gets productized. If you can drive turning a set of ambitious but loosely defined initiatives into a predictable, well-governed program, this role is for you.

EXAMPLE INITIATIVES

Take a look at these blog posts written by members of our Model Performance team:

  • How to build a day-0 API for Kimi K3 baseten.co
  • How we built the new fastest API for GLM-5.2 baseten.co
  • Inference engineering for DeepSeek V4 Pro 0813 baseten.co

RESPONSIBILITIES

  • Own execution across Model Performance's active project portfolio, freeing the team's technical leads to focus on technical direction rather than tracking.
  • Design and stand up the planning structures, operating cadences, and status reporting mechanisms that best fits the team’s DNA.
  • Coordinate model release and optimization programs end to end, including day-zero launches, sequencing the work across performance engineering, infra, and release stakeholders.
  • Drive cross-team alignment as scope expands from Model Performance Core into Model APIs and the inference production stack (BIS).
  • Surface risks and dependencies early, and keep leadership informed with clear, honest status.
  • Partner with engineering leads to design team structures and ownership boundaries as the org scales.

REQUIREMENTS

  • Deep technical program management experience - you're already running programs of this scope at an organization of similar or greater complexity.
  • Experience program-managing model performance or inference optimization work - you understand how engines like vLLM, TensorRT-LLM, SGLang, or NVIDIA Dynamo fit into a production serving stack and can engage credibly with the engineers building on them.
  • Demonstrated comfort with ambiguity and zero-to-one program building, not just executing an existing framework.
  • Proven ability to influence without authority across engineers, managers, and leadership who don't report to you.
  • Excellent written and verbal communication, with the ability to make deeply technical programs legible to any audience.
  • High agency decision making that demonstrates ownership, accountability and a strong desire to get things done.

NICE TO HAVE

  • Experience coordinating model release programs, including day-zero launches (ideally for large-scale models).
  • Prior hands-on software engineering background.
  • Deep learning performance optimization background, in training or inference, with inference preferred.

BENEFITS

  • 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.

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).

Why work at Baseten

  • Hard Technical Problems: Engineers work on the most challenging problems in modern infrastructure—model serving, low-level GPU optimization, networking, distributed systems, and observability. This is a high-agency, high-impact engineering environment.
  • High Growth Trajectory: The company is experiencing explosive growth (224% headcount increase, active hiring). This offers significant career acceleration and ownership opportunities.
  • Strong Engineering Culture: Founded by engineers, for engineers. The culture emphasizes "first-principles thinking across the entire stack" and a "customer-obsessed" mindset. The employer rating on compensation, culture, and work-life balance is rated highly (5.0).
  • Top-Tier Team & Investors: The team has strong talent density with hires from Meta, Stripe, Google, NVIDIA, and Databricks. Being backed by top-tier VCs provides stability and a clear long-term vision.
  • Hybrid/In-Office: Based in San Francisco with a strong in-person or hybrid culture common for fast-moving infrastructure startups.

Application questions