# ML Solution Architect (Early Talent)

**Company**: Nebius
**Location**: United States
**Work arrangement**: remote
**Experience**: entry
**Job type**: temporary
**Salary**: $102-$126 USD
**Category**: Engineering
**Industry**: Technology

**Apply**: https://job-boards.greenhouse.io/nebius/jobs/4883829101?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/jobs/job_82beaa7d-b6d

## Description

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. You will work alongside senior Solutions Architects, taking 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.

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.

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 (K8s), Docker, Git.

- Cloud Platforms – AWS (SageMaker, Bedrock), GCP (Vertex AI), Azure (Azure ML).

Benefits:

- 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.

## Skills

### Required
- Python
- Machine Learning
- Generative AI
- PyTorch
- Transformers
- Communication

### Nice to have
- vLLM
- SGLang
- TensorRT-LLM
- Inference Optimization
- Model Architectures
- Fine-tuning Approaches
- Open-source ML/AI projects

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Source: [Apply at job-boards.greenhouse.io](https://job-boards.greenhouse.io/nebius/jobs/4883829101?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)