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Salary analysis
Compared with the selected benchmark ("Company in Remote - United States"), this listing's salary midpoint is about 784% higher. The offer sits above the benchmark range (€1,667–€2,153). The offer's range width is broadly in line with the benchmark. This benchmark is based on 3 comparable listings.
| Market | Lower bound (25th percentile) | Median | Upper bound (75th percentile) |
|---|---|---|---|
| Market Average: Technical Account Manager | €905/per month | €1,182/per month | €1,459/per month |
| Company in Remote - United States | €1,667/per month | €1,910/per month | €2,153/per month |
| From job ad (Manager) | €15,000/per month | €16,875/per month | €18,750/per month |
The role\nWe're looking for a Technical Account Manager (TAM) 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.\nThis 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.\nThis role is NOT:\nA sales role (though you will support expansion through value)\nA pure support role (you won’t just react to tickets)\nA solution architect role (you won’t design systems from scratch)\nYou’re welcome to work remotely from the United States.\nYour responsibilities will include: \nOwn the production journey\n• Lead the transition from PoC to production\n• Ensure customer workloads are deployed, stable, and scalable\n• Drive time-to-production and time-to-value\nEnsure technical success in production\n• Understand customer architectures and use cases\n• Monitor and improve:\no performance (latency, throughput)\no cost efficiency\no reliability\n• Identify and resolve bottlenecks proactively\nAct as a trusted technical partner\n• Work directly with customer engineering teams\n• Provide guidance on best practices and optimisation\n• Translate technical challenges into actionable solutions\nManage risks and incidents\n• Act as a primary technical contact for production issues\n• Coordinate with internal teams to resolve incidents\n• Communicate clearly during high-pressure situations\nDrive continuous improvement\n• Identify opportunities to optimise and expand usage\n• Provide structured feedback to Product and Infrastructure teams\n• Help shape better solutions based on real customer needs\nWe expect you to have: \nTechnical background\nPractical knowledge of inference frameworks (e.g. vLLM, TensorRT, or similar)\nSolid understanding of:\n- cloud or infrastructure systems\n- distributed systems or high-load applications\n- AI/ML workloads (LLMs, inference, etc.) is a strong plus\nAbility to troubleshoot and reason about system performance\nCustomer-facing experience\nExperience working directly with technical customers (e.g. engineers, ML teams)\nAbility to communicate complex topics clearly and effectively\nOwnership & execution\nStrong sense of ownership – you drive outcomes, not just tasks\nAbility to manage multiple customers and priorities\nStructured, proactive, and solution-oriented mindset\nIt will be an added bonus if you have: \nExperience with GPU workloads or AI infrastructure\nBackground in solutions engineering, SRE, or technical support in B2B environments\nKey employee benefits:\nHealth insurance: 100% company-paid medical, dental, and vision coverage for employees and families.\n401(k) plan: Up to 4% company match with immediate vesting.\nParental leave: 20 weeks paid for primary caregivers, 12 weeks for secondary caregivers.\nRemote work reimbursement: Up to $85/month for mobile and internet.\nDisability & life insurance: Company-paid short-term, long-term and life insurance coverage.\n#LI-DK1\nPay Transparency\nWe 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.\nBase Compensation Range\n$180,000 - $225,000 USD\nBenefits & Perks:\nCompetitive compensation\nCareer growth and learning opportunities\nFlexibility and ownership\nCollaborative and innovative culture\nOpportunity to work on impactful AI projects\nInternational environment and talented teams\nWhat\'s it like to work at Nebius:\nFast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI \nEqual Opportunity Statement:\nNebius 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.\nApplicants 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. \nIf you need accommodations during the application process, please let us know.
Job Details
Responsibilities
- Lead the transition from PoC to production
- Ensure customer workloads are deployed, stable, and scalable
- Drive time-to-production and time-to-value
- Understand customer architectures and use cases
- Monitor performance, cost efficiency and reliability
- Identify and resolve bottlenecks proactively
- Work directly with customer engineering teams
- Provide guidance on best practices and optimisation
- Translate technical challenges into actionable solutions
- Act as a primary technical contact for production issues
- Coordinate with internal teams to resolve incidents
- Communicate clearly during high-pressure situations
- Identify opportunities to optimise and expand usage
- Provide structured feedback to Product and Infrastructure teams
- Help shape better solutions based on real customer needs
Requirements
- 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 experience
- AI/ML workloads
Skills & Technologies

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