ML Solution Architect (Early Talent)

: Remote from USA
Duration: 3 months

: 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.

• 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. 

• 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. 

• 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). 

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