ML Solution Architect (Early Talent)

Details

About Nebius:

Nebius is building a full-stack AI cloud platform for the global AI economy, supporting developers and enterprises from data and model training through production deployment. The company focuses on large-scale GPU orchestration, inference optimization, and owns problems across compute, storage, networking and applied AI. Nebius is listed on Nasdaq (NBIS) and headquartered in Amsterdam with R&D hubs across Europe, the UK, North America and Israel. The team includes 1,500+ people with deep expertise across hardware, software and AI R&D.

Summary

• Location: Remote from United States (remote work from any timezone is welcomed)
• Duration: 3 months (paid temporary contract)
• Compensation: Paid (Base Compensation Range shown: $102 — $126 USD)
• Eligibility: Current university student (Computer Science or related field), recent graduate, or early career specialist
• Work authorization: Must be permitted/authorized to work in the job's location and able to provide proof of employment eligibility

This is a hands-on learning role with close mentorship from senior Solutions Architects. Strong performers will be considered for a full-time Solutions Architect position at the end of the program.

Responsibilities

• Help build and test LLM-based solutions and applications using Token Factory's inference services, including multimodal models (text, vision, audio).
• Assist senior Solutions Architects with prompt engineering, model selection, benchmarking, and inference optimization.
• Run performance and quality experiments to support proof-of-concept work.
• Contribute to internal tooling and automation that improves how the Solutions Architect team delivers.

Requirements

Must-haves

• Currently pursuing or recently completed a BSc/MSc/PhD in Computer Science, Machine Learning, or a related field.
• Strong Python programming skills.
• Hands-on generative AI experience, including with common ML frameworks (e.g., PyTorch, Transformers).
• Strong communication skills and willingness to explain technical concepts to diverse audiences.

Nice-to-haves

• Experience deploying/serving LLMs with vLLM, SGLang, or TensorRT-LLM.
• Familiarity with inference optimization techniques such as quantization, batching, caching, and routing.
• Knowledge of model architectures and fine-tuning approaches.
• Contributions to open-source ML/AI projects.

Preferred technical stack

• Programming languages: Python
• ML frameworks and libraries: vLLM, SGLang, TensorRT-LLM, Transformers, OpenAI/Anthropic SDKs
• Frameworks for agentic pipelines: LangChain / Langsmith / smolagents / equivalent
• API and web frameworks: FastAPI, Flask
• MLOps and DevOps tools: Kubernetes, Docker, Git
• Cloud platforms: AWS (SageMaker, Bedrock), GCP (Vertex AI), Azure (Azure ML)

Pay Transparency

Base Compensation Range: $102 — $126 USD (as provided in the posting). Actual compensation will be determined based on job-related factors including experience, skills, qualifications, level at hire, and geographic location.

Benefits

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.

Additional perks listed: 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.