Nebius

Senior ML Solutions Architect - Token Factory

Remote remote Senior Salary not listed
remote Senior level Technology & IT Curated
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About the role

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
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 (LoRA, full FT, RFT) 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.
We seek an experienced Senior ML Solutions Architect to support customers leveraging Nebius Token Factory's serverless inference and fine-tuning platforms for open-source LLMs across multiple modalities. In this role, you will be collaborating with clients to design and implement optimized inference workflows, build customized LLM-based solutions and architect scalable AI applications using our served models. You will also work closely with our backend team to improve our platform to match clients' needs.
You’re welcome to work remotely from Europe.
Your responsibilities will include:

Optimize LLM inference across various modalities to drive business value and support customer goals

Provide support in supervised and reinforcement learning fine-tuning to maximize model quality for the customers

Design and implement LLM-based solutions using Nebius Token Factory’s inference services

Build production-ready applications leveraging our serverless LLM APIs, including multimodal models (text, vision, audio) and domain-specific models

Provide technical expertise in prompt engineering, RAG architectures and model selection

Collaborate with product and engineering teams to surface customer feedback and shape the platform roadmap

Guide customers in scaling from POC to production with a focus on performance, reliability, and cost efficiency

We expect you to have:

5+ years of experience in ML/AI systems, with at least 2 years focused on LLMs and generative AI

Deep knowledge of the LLM ecosystem, including model architectures and fine-tuning approaches

Hands-on experience with:

Running LLMs in production: deploying and operating inference workloads

LLM fine-tuning, including supervised fine-tuning (SFT/LoRA) and data preparation/curation; experience with RL-based fine-tuning is a strong plus

LLM evaluation: building task-specific benchmarks and offline/online eval pipelines, including LLM-as-a-judge setups

Inference frameworks and libraries (e.g., vLLM, SGLang, TensorRT-LLM, Transformers)

Deploying LLM-powered applications using APIs from OpenAI, Anthropic, or open-source models

Strong Python programming skills

Excellent communication skills, with the ability to clearly explain technical concepts to diverse audiences

It would be an added bonus if you have:

Work with multimodal AI models (e.g., vision-language, speech)

Proficiency with DevOps tools (Docker, Kubernetes)

Contributions to open-source ML/AI projects

Preferred technical stack:

Programming Languages: Python

ML Frameworks and Libraries: vLLM, TensorRT-LLM, SGLang, Transformers, OpenAI/Anthropic SDKs

MLOps and DevOps tools: Kubernetes (K8s), Docker, Git

Cloud Platforms: AWS (SageMaker, Bedrock), GCP (Vertex AI), Azure (Azure ML)

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.

Originally posted on Himalayas

Interview prep

Walk in with sharper answers.

Use this as a quick practice sheet before you speak with the employer.

Senior
Technology & IT Figma Python Senior Solutions Architect Senior level

Likely questions

  1. Tell us about work you have done that is close to the Senior ML Solutions Architect - Token Factory role.
  2. How would you approach your first 30 days at Nebius?
  3. Which of Figma, Python and Senior have you used recently, and what did it help you achieve?
  4. How have you led people, improved a process, or made a hard decision in a previous role?
  5. How do you stay organised and communicate clearly when working remotely?

Prepare before the call

  • A recent example that proves your experience with Figma, Python and Senior.
  • One short story with a problem, your action, and the result.
  • Two examples that show the strengths listed on your CV.
  • A clear reason why this role and company interest you.
  • Your availability, preferred work style, and salary expectations.

Ask them

  • What would success look like in the first 90 days?
  • What are the main problems this hire should help solve?
  • How does the team give feedback and measure good work?
  • What does a normal working week look like for this role?
Practice line

I am interested in the Senior ML Solutions Architect - Token Factory role because I can bring practical experience in Figma, Python and Senior, learn the team quickly, and contribute to the outcomes Nebius needs from this hire.

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