ML Solution Architect (Early Talent)

About the role

Location : Remote from USA Duration : 3 months Compensation : Paid Eligibility : Current University student (Computer Science or related field), Recent Graduate or Early Career specialist Work authorization : permitted to work in the job's location We're looking for an ML Solutions Architect (Early Career) to join the team behind Nebius Token Factory's serverless inference and fine-tuning platform for open-source LLMs. Working alongside senior Solutions Architects, you'll take on real technical work - building and testing LLM-based solutions, benchmarking, and inference optimization - and learn how scalable AI applications are built and tuned on our platform, in close collaboration with our backend team. This is a hands-on learning role with close mentorship from senior SAs. Strong performers will be considered for a full-time Solutions Architect position at the end of the program. This is a paid temporary contract , open to students and recent graduates. You're welcome to work remotely from any timezone.

Responsibilities

• Help build and test LLM-based solutions and applications using Token Factory's inference services, including multimodal models (text, vision, audio).
• Assist senior SAs 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 SA team delivers.

Requirements

• 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, with a willingness to explain technical concepts to diverse audiences.
• 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 (K8s), Docker, Git.
• Cloud Platforms - AWS (SageMaker, Bedrock), GCP (Vertex AI), Azure (Azure ML).
• 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.
• 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
• $102 - $126 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:

Benefits

Additional Information

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.

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