Senior Technical Program Manager – LLM Inference
Company websitenebius.com (Nebius, opens in new tab)
Base salary $147,200 to $224,000
Employer-published annual base salary, USD. Advertised base range in Palo Alto, CA
You apply on the employer's own site. Six Figure Work does not handle applications.
- LocationPalo Alto, CA
- WorkplaceWorkplace not stated
- Status at last checkSource accepting applications when checked
- Last checked (1 h ago) · observed since
About this job
About Nebius:
Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure.
Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI.
Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D.
Role
As a Technical Program Manager in Token Factory, your primary focus will be coordinating complex cross-functional projects, including new model launches, bringing new GPU platforms into production serving, engineering quality and platform-wide improvement projects, and the end-to-end delivery pipeline for new AI models. You will bring together multiple engineering teams, understand the critical path, proactively manage dependencies and risks, and ensure that ambitious technical goals are delivered predictably, on time, and without unnecessary operational overhead.
Your responsibilities will include:
- Leading template and model delivery — from weights through validation to production endpoint.
- Coordinating model onboarding and production delivery, from infrastructure readiness to successful customer availability.
- Running the Applied AI / Customer Delivery sync — driving open issues to resolution and unblocking teams between meetings.
- Coordinating the bring-up of new GPU platforms for serving — engine and kernel readiness, benchmarking against current hardware, and template migration once validated.
- Partnering with Token Factory Product on the serverless launch path — ensuring validated templates hand off cleanly into catalogue, model card, and public availability.
- Building and maintaining execution plans, identifying risks early, and ensuring blockers are resolved before they impact delivery.
- Working closely with engineering managers, technical leads, product managers, SRE, infrastructure, networking, security, and other platform teams.
- Facilitating technical decision-making and ensuring ownership and accountability across complex cross-team projects.
- Continuously improving engineering delivery processes within Applied AI's delivery chain to make execution more predictable while maintaining a sustainable pace for engineering teams.
Requirements
- Excellent project management and delivery skills with the ability to break down ambiguous initiatives into executable plans
- Ability to identify critical paths, manage complex dependency graphs, and coordinate multiple parallel workstreams
- Strong risk management and prioritization skills, with the ability to make progress in fast-changing environments
- Excellent written and verbal communication skills in English
- Comfortable leading incident coordination, facilitating discussions, documenting decisions, and driving follow-up actions
- Strong technical background that allows you to understand engineering discussions, infrastructure dependencies, and architectural trade-offs without being the primary implementer
It will be an added bonus if you have
- Experience working with GPU infrastructure, AI/ML platforms, or large-scale inference systems
- Experience delivering cloud infrastructure or data center deployment projects
- Familiarity with capacity planning, production operations, and reliability engineering
- Previous experience in high-growth infrastructure or platform engineering organizations where priorities change quickly and execution speed matters
Pay Transparency
We offer competitive compensation and benefits packages. Actual compensation will be determined based on job-related factors, including experience, skills, qualifications, the level at which the candidate is hired, and geographic location, consistent with applicable law.
Base Compensation Range
$147,200—$224,000 USD
Benefits & Perks:
- Competitive compensation
- Career growth and learning opportunities
- Flexibility and ownership
- Collaborative and innovative culture
- Opportunity to work on impactful AI projects
- International environment and talented teams
What's it like to work at Nebius:
Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI
Equal Opportunity Statement:
Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law.
Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire.
If you need accommodations during the application process, please let us know.
Source: Nebius on Greenhouse · View original posting (opens in new tab)
Pay in context
This role's base floor ($147,200) is above 15% of the 1,493 Data & ML roles in California listed on this site. Their median floor is $190,000; the middle half runs from $160,000 to $229,900.
Only jobs on this site count, and each one publishes a base salary of $100,000 or more, so this compares six-figure jobs with each other, not with the whole market. Computed Nov 6, 2026.
This listingSenior Technical Program Manager – LLM Inference$147,200 to $224,000
L3 Support Engineer, Data Center Infrastructure$147,200 to $183,900
L3 Support Engineer, Data Center Infrastructure$147,200 to $183,900
L3 Support Engineer, Data Center Infrastructure$147,200 to $183,900
Senior Enterprise Applications Engineer$147,200 to $183,900
Senior SWE (Agentic Search) - Billing$147,200 to $224,300
Senior Full Stack Engineer (Agentic Search) - Platform$147,200 to $224,300
Chart as a table
| Role | Published base |
|---|---|
| Senior Technical Program Manager – LLM Inference (this listing) | $147,200 - $224,000 |
| L3 Support Engineer, Data Center Infrastructure | $147,200 - $183,900 |
| L3 Support Engineer, Data Center Infrastructure | $147,200 - $183,900 |
| L3 Support Engineer, Data Center Infrastructure | $147,200 - $183,900 |
| Senior Enterprise Applications Engineer | $147,200 - $183,900 |
| Senior SWE (Agentic Search) - Billing | $147,200 - $224,300 |
| Senior Full Stack Engineer (Agentic Search) - Platform | $147,200 - $224,300 |
Observed changes
- Began meeting the published-salary criteria
- First observed on the employer's board
- Observed since
- Employer-stated posting date
- 2026-08-10
Where this pay comes from
Location as the employer wrote it: Palo Alto, California, United States
USD 147,200 – 224,000 · interval unstated · pay_input_range · Base Compensation Range · base-labelled (R1: Base Compensation)
- Method
- Structured pay field published by the employer
- Checked
- Rule set
- us-base-v2
The employer's job board publishes this pay as a dedicated data field. We read the field directly; no interpretation was needed.
What we verified
- The pay figures come from the employer's own listing, quoted exactly above.
- The pay is an annual base salary in US dollars with a minimum of at least $100,000.
- The role was publicly listed on the employer's job board when last checked.
We do not verify what the employer will actually offer, whether the employer is still recruiting for the role, or anything beyond what the employer published. Full methodology.
