Six Figure Work

Senior Customer AI Engineer - Token Factory

Nebius

Company websitenebius.com (Nebius, opens in new tab)

Base salary $209,800  to $262,200

Employer-published annual base salary, USD. Advertised base range in United States

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  • LocationUnited States
  • WorkplaceWorkplace not stated
  • Status at last checkSource accepting applications when checked
  • Last checked (2 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.

The role

We're looking for a Senior Customer AI Engineer who will join our Token Factory team to help our customers successfully transition from proof-of-concept to production and scale their AI workloads on Nebius infrastructure.

This role sits at the intersection of engineering, delivery, and customer success – ensuring that what was promised during pre-sales actually works reliably in production. You will work closely with customer engineering teams, Solution Architects, and Product/Infrastructure teams to drive stable, performant, and cost-efficient deployments.

This role is NOT:

  • A sales role (though you will support expansion through value)
  • A pure support role (you won’t just react to tickets)
  • A solution architect role (you won’t design systems from scratch)

You’re welcome to work remotely from the United States.

Your responsibilities will include: 

Own the production journey

  • Lead the transition from PoC to production
  • Ensure customer workloads are deployed, stable, and scalable
  • Drive time-to-production and time-to-value

Ensure technical success in production

  • Understand customer architectures and use cases
  • Monitor and improve:
    - performance (latency, throughput)
    - cost efficiency
    - reliability
  • Identify and resolve bottlenecks proactively

Act as a trusted technical partner

  • Work directly with customer engineering teams
  • Provide guidance on best practices and optimisation
  • Translate technical challenges into actionable solutions

Manage risks and incidents

  • Act as a primary technical contact for production issues
  • Coordinate with internal teams to resolve incidents
  • Communicate clearly during high-pressure situations

Drive continuous improvement

  • Identify opportunities to optimise and expand usage
  • Provide structured feedback to Product and Infrastructure teams
  • Help shape better solutions based on real customer needs

We expect you to have: 

Technical background

  • Practical knowledge of inference frameworks (e.g. vLLM, TensorRT, or similar)
  • Solid understanding of:
    - cloud or infrastructure systems
    - distributed systems or high-load applications
    - AI/ML workloads (LLMs, inference, etc.) is a strong plus
  • Ability to troubleshoot and reason about system performance

Customer-facing experience

  • Experience working directly with technical customers (e.g. engineers, ML teams)
  • Ability to communicate complex topics clearly and effectively

Ownership & execution

  • Strong sense of ownership – you drive outcomes, not just tasks
  • Ability to manage multiple customers and priorities
  • Structured, proactive, and solution-oriented mindset

It will be an added bonus if you have: 

  • Experience with GPU workloads or AI infrastructure
  • Background in solutions engineering, SRE, or technical support in B2B environments

Key employee benefits in the US:

  • Health insurance: 100% company-paid medical, dental, and vision coverage for employees and families.
  • 401(k) plan: Up to 4% company match with immediate vesting.
  • Parental leave: 20 weeks paid for primary caregivers, 12 weeks for secondary caregivers.
  • Remote work reimbursement: Up to $85/month for mobile and internet.
  • Disability & life insurance: Company-paid short-term, long-term and life insurance coverage.

#LI-DN1

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

$209,800—$262,200 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 ($209,800) is above 81% of the 4,591 Data & ML roles nationwide listed on this site. Their median floor is $165,000; the middle half runs from $135,000 to $198,000.

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 7, 2026.

This range next to 6 other live Nebius roles with the nearest advertised base floor
Chart as a table
This range next to 6 other live Nebius roles with the nearest advertised base floor
RolePublished base
Senior Customer AI Engineer - Token Factory (this listing)$209,800 - $262,200
Field CTO, Financial Services AI Infrastructure$210K - $260K
Principal ML Solutions Architect - Token Factory$208K - $261K
Legal Counsel (US Infrastructure)$206,400 - $258,000
Technology Commercial Legal Counsel$206,400 - $258,000
Technology Commercial Legal Counsel$206,400 - $258,000
Senior Applied Scientist, Efficient LLM Inference & Model Optimization$195,200 - $262,200

Same $100K to $400K scale as every card. All Nebius roles · How to read the bar

Observed changes

  1. First observed on the employer's board
  2. Began meeting the published-salary criteria
Observed since
Employer-stated posting date
2026-10-12
Where this pay comes from

Location as the employer wrote it: United States (remote)

USD 209,800 – 262,200 · 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.

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