Senior Technical Project Manager – Applied AI

Posted Yesterday
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Palo Alto, CA, USA
In-Office
147K-224K Annually
Senior level
Artificial Intelligence • Information Technology • Consulting
The Role
Lead and coordinate cross-functional applied AI infrastructure and model delivery projects, including region launches, capacity expansion, and model onboarding. Build execution plans, manage dependencies and risks, facilitate technical decision-making, and improve engineering delivery processes while working with engineering, SRE, infrastructure, networking, security, and product teams.
Summary Generated by Built In

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 Project Manager for Applied AI in Token Factory, your primary focus will be coordinating complex cross-functional projects, including new region launches, 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 infrastructure and capacity delivery projects, including new region deployments, capacity expansion, or maintenance framework initiatives. 
  • Coordinating model onboarding and production delivery, from infrastructure readiness to successful customer 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 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.

Skills Required

  • Excellent project management and delivery skills; 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; 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 to understand engineering discussions, infrastructure dependencies, and architectural trade-offs
  • Authorization to work in the country of application (must provide proof of employment eligibility)
  • 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
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The Company
HQ: Amsterdam
473 Employees

What We Do

Cloud platform specifically designed to train AI models

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