[Hiring] Manager, ML Solutions Architecture @Nebius

Role Description

This position sits within Nebius Token Factory, our serverless platform for running and customizing open-source LLMs in production. Token Factory allows for serverless inference and fine-tuning backed by in-house optimizations like custom speculative decoding, quantization, cache-aware routing, and dedicated endpoints. Customers come to us to move from prototype to scaled production without the cost and complexity of building and tuning their own inference stack.

Our Solutions Architects own the technical delivery of customer engagements:

• Deploying open-source models
• Tuning the serving stack
• Benchmarking against the customer's success criteria
• Carrying the technical relationship through to production

We're looking for a Manager, ML Solutions Architecture to lead our EU regional SA teams. Your scope is PoC delivery and post-sales technical support:

• Manage a team of 8 Solutions Architects
• Report to the Head of Solutions Architecture
• Partner with a peer manager in the other region

Your responsibilities will include:

• Lead the team
• Build an accurate picture of each SA's strengths, gaps, and preferences
• Run the cadence that surfaces blockers early
• Hold people to outcomes
• Onboard new joiners through to their first independently delivered engagement
• Coach SAs into stronger engineers and communicators

Own delivery:

• Be accountable for your team's delivery outcomes
• Review technical work before it reaches the customer
• Ensure staffing and escalation coverage across accounts and timezones
• Call infeasibility early and with evidence

Own the operating system of the team:

• Maintain and extend the team's documentation
• Get it used, not just written
• Keep the ticket tracker the system of record
• Instrument the work

Work across teams:

• Convert recurring customer pain into prioritized platform work
• Hold the scoping-to-execution boundary
• Make production handoffs uneventful
• Give a straight read on account health, technical feasibility, and capacity needs

Qualifications

• 3+ years managing technical teams, including performance management and difficult conversations
• Experience managing a customer-facing team
• Strong ML knowledge: LLM architectures, fine-tuning approaches, evaluation design
• Technical judgment to review benchmarks and methodologies
• Python strong enough to read and review your team's code
• Excellent communication skills
• Genuine tolerance for operational work
• Comfort operating with ambiguity across distributed teams and timezones

Requirements

• References from both former managers and former direct reports
• Experience scaling a team through rapid growth
• Prior experience in a customer-facing technical function at a cloud, inference, or AI infrastructure provider
• Experience defining process and documentation for a team that had none
• Hands-on background running LLMs in production
• Work with multimodal AI models
• Proficiency with DevOps tooling and infrastructure-as-code

Benefits

• 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