# Principal ML Solutions Architect - Token Factory

**Company**: Nebius
**Location**: United States
**Work arrangement**: remote
**Experience**: senior
**Job type**: full-time
**Salary**: $208,000-$261,000 USD
**Category**: Engineering
**Industry**: Technology

**Apply**: https://job-boards.greenhouse.io/nebius/jobs/5000579101?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/jobs/job_f25927c7-0b3

## Description

We are looking for a Principal ML Solutions Architect to act as the most senior technical authority for customers leveraging Token Factory's serverless inference and fine-tuning platforms.

The successful candidate will design and implement optimized inference and fine-tuning workflows, set technical direction across our largest and most strategic accounts, own the hardest performance and quality problems end to end, mentor other Solutions Architects, and serve as a primary technical voice shaping the platform roadmap with backend, product, and research teams.

Responsibilities:

- Own the most complex, highest-stakes customer engagements from architecture through production across multiple modalities, driving measurable business value

- Optimize LLM inference at the framework and hardware level and codify the resulting best practices into reusable playbooks for the team

- Lead supervised and reinforcement fine-tuning efforts to maximize model quality

- Design and implement production-ready LLM solutions using Token Factory's inference services

- Provide deep technical expertise in prompt engineering, RAG architectures, model selection, and cost/performance trade-offs at scale

- Partner closely with product, engineering and research to surface customer needs, prototype platform features, and directly influence the roadmap

- Guide customers from PoC to production with a focus on performance, reliability, and cost efficiency , and define the standards by which the team does so

- Mentor Senior and mid-level Solutions Architects; raise the technical bar of the team through review, enablement, and knowledge sharing

- Represent Token Factory externally through talks, blog posts, and conferences

Requirements:

- 8+ years of experience in ML/AI systems, with at least 4 years focused on LLMs and generative AI

- Demonstrated technical leadership: owning ambiguous, high-impact problems end to end and influencing decisions across teams and customers

- Expert knowledge of the LLM ecosystem: model architectures, fine-tuning approaches, and inference internals

- Deep, hands-on command of inference optimization: quantization, KV-cache management, batching, routing, etc.

- Hands-on experience with:

- Running LLMs in production at scale: deploying, operating, and debugging inference workloads down to the framework level

- LLM fine-tuning, including SFT/LoRA and data preparation/curation; experience with RL-based fine-tuning

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

- Inference frameworks and libraries (vLLM, SGLang, TensorRT-LLM), including the ability to read, modify, and contribute to their internals

- 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, from engineers to executives

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
- LLM ecosystem
- inference optimization
- quantization
- KV-cache management
- batching
- routing
- LLM fine-tuning
- SFT/LoRA
- data preparation/curation
- RL-based fine-tuning
- LLM evaluation
- benchmarks
- offline/online eval pipelines
- LLM-as-a-judge setups
- inference frameworks
- libraries (vLLM, SGLang, TensorRT-LLM)
- OpenAI
- Anthropic
- open-source models

### Nice to have
- Contributions or maintainership in major OSS inference/ML projects (vLLM, SGLang, TensorRT-LLM)
- Published research
- conference talks
- widely-read technical writing in the LLM/serving space
- multimodal AI models (vision-language, speech)
- Proficiency with DevOps tooling (Docker, Kubernetes) and infrastructure-as-code
- Experience building or owning internal tooling/automation for ML workflows at scale

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Source: [Apply at job-boards.greenhouse.io](https://job-boards.greenhouse.io/nebius/jobs/5000579101?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)