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Technical Program Manager, Model Performance
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Baseten·San Francisco·29 авг.

Technical Program Manager, Model Performance

🏢 ОфисMiddleПолная занятость
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Наша компания

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 to ship AI products.

О роли

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

Чем предстоит заниматься

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
How we built the new fastest API for GLM-5.2
Inference engineering for DeepSeek V4 Pro 0813
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

Наши требования

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
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

Мы предлагаем

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
B
Baseten
San Francisco

ГрейдMiddle
ЗанятостьПолная занятость
РегионНе Россия
ФорматОфис
ИсточникСкрыто
Опубликовано29 авг.
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