Technical Program Manager, Model Performance

Rozgoo; United States; Remote; USD 180,000 - 230,000; Full time

Benefits offered by this job

Competitive compensation & equity

Medical, dental, vision insurance (US)

Flexible PTO including Winter Break

Parental leave

Fertility and family-building stipend

401(k)

Job summary

Baseten is hiring its first Technical Program Manager in the Model Performance organization. This zero-to-one role builds the planning structures, cadences, and status reporting that enable fast, well-governed productization of performance R&D.

You will own end-to-end model release and optimization programs, coordinate across performance engineering, infra, and release stakeholders, and shape org structures as Baseten scales.

Qualifications

• Deep technical program management experience in a complex org.
• Experience program-managing model performance or inference optimization work.
• Comfort with ambiguity and zero-to-one program building.
• Ability to influence without authority across engineers, managers, and leadership.
• Excellent written and verbal communication, making technical programs legible.
• High agency and ownership to drive results.

Responsibilities

• Own execution across Model Performance's active project portfolio.
• Design and stand up planning structures, cadences, and status reporting mechanisms.
• Coordinate model release and optimization programs end-to-end, including day-zero launches.
• Drive cross-team alignment as scope expands to Model APIs and inference production stack.
• Surface risks and dependencies early and keep leadership informed with status.
• Partner with engineering leads to design team structures and ownership boundaries as the org scales.

Skills

Technical program management

Cross-functional leadership

Effective communication

Ownership & accountability

Tools

vLLM

TensorRT-LLM

SGLang

NVIDIA Dynamo

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 , 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.

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 (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.

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).