OperationsHybrid

Technical Program Manager, Model Performance

Baseten · Hybrid

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Last seen by MeritLog September 9, 2026Source: AshbySource version: ashby-public-job-posting-v1

MeritLog read this listing from Baseten's Ashby job board and last checked it on September 9, 2026.

Source: the employer's Ashby job board. Open the original listing for current details.

Job details

Work model: Hybrid
Salary: $165K - $330K
Location: San Francisco
Company website: www.baseten.co

Hiring context

How this role compares at Baseten

Baseten has 87 live roles in MeritLog’s catalog across 9 job families, and 5 of them are in operations. 87 of those listings publish a pay range, a disclosure rate of 100%.

This role's posted range of $165K - $330K sits above 51% of the 85 other Baseten roles quoted over the same currency and period.

Baseten concentrates this hiring in:

Counted across the job boards MeritLog tracks, at the time this page was served. Pay comparisons use only listings that publish a complete range in the same currency and period.

What the role asks for

What you'd do

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.

What they're asking for

Deep technical program management experience - you're already running programs of this scope at an organization of similar or greater complexity.Skill
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.Skill
Demonstrated comfort with ambiguity and zero-to-one program building, not just executing an existing framework.Skill
Proven ability to influence without authority across engineers, managers, and leadership who don't report to you.Skill
Excellent written and verbal communication, with the ability to make deeply technical programs legible to any audience.Skill
High agency decision making that demonstrates ownership, accountability and a strong desire to get things done.Skill
Experience coordinating model release programs, including day-zero launches (ideally for large-scale models).SkillPreferred
Prior hands-on software engineering background.SkillPreferred
Deep learning performance optimization background, in training or inference, with inference preferred.SkillPreferred

Parsed by MeritLog from the employer’s own posting. The full description follows below.

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 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 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 https://www.baseten.co/blog/how-to-build-a-day-zero-api-for-kimi-k3/ - How we built the new fastest API for GLM-5.2 https://www.baseten.co/blog/how-we-built-the-new-fastest-api-for-glm-52/ - Inference engineering for DeepSeek V4 Pro 0813 https://www.baseten.co/blog/inference-engineering-for-deepseek-v4-pro-0813/ 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).

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