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Monthly
€15,192 - €18,809
Posted August 26, 2026 · 0 days agoLast seen August 26, 2026Est. expiry September 30, 2026

Senior ML Solutions Architect

Senior ML Solutions Architect - Token Factory
Remote - United States
Remote · Technology
Full-time · Executive
English
No People Management
5 years experience
How this salary compares
Salary Context: Senior ML Solutions Architect

Hover or tap a row for full statistics (EUR / month on this chart).

Salary analysis

Compared with the selected benchmark ("Company in Remote - United States"), this listing's salary midpoint is about 925% higher. The offer sits above the benchmark range (€1,667–€2,153). The offer's range width is broadly in line with the benchmark. This benchmark is based on 3 comparable listings.

Monthly salary comparison for Senior ML Solutions Architect
MarketLower bound (25th percentile)MedianUpper bound (75th percentile)
All roles in Remote - United States€1,667/per month€10,711/per month€17,242/per month
Company in Remote - United States€1,667/per month€1,910/per month€2,153/per month
From job ad (Executive)€17,500/per month€19,583/per month€21,667/per month
About the role

This position sits within Nebius Token Factory, our serverless platform for running and customizing open-source LLMs in production. Token Factory allows for serverless inference and fine-tuning (LoRA, full FT, RFT) backed by in-house optimizations like custom speculative decoding, quantization, cache-aware routing and dedicated endpoints. Customers come to us to move from prototype to scaled production without the cost and complexity of building and tuning their own inference stack. We seek an experienced Senior ML Solutions Architect to support customers leveraging Nebius Token Factory's serverless inference and fine-tuning platforms for open-source LLMs across multiple modalities. In this role, you will be collaborating with clients to design and implement optimized inference workflows, build customized LLM-based solutions and architect scalable AI applications using our served models. You will also work closely with our backend team to improve our platform to match clients' needs. You’re welcome to work remotely from the United States. Your responsibilities will include: - Optimize LLM inference across various modalities to drive business value and support customer goals - Provide support in supervised and reinforcement learning fine-tuning to maximize model quality for the customers - Design and implement LLM-based solutions using Nebius Token Factory’s inference services - Build production-ready applications leveraging our serverless LLM APIs, including multimodal models (text, vision, audio) and domain-specific models - Provide technical expertise in prompt engineering, RAG architectures and model selection - Collaborate with product and engineering teams to surface customer feedback and shape the platform roadmap - Guide customers in scaling from POC to production with a focus on performance, reliability, and cost efficiency We expect you to have: - 5+ years of experience in ML/AI systems, with at least 2 years focused on LLMs and generative AI - Deep knowledge of the LLM ecosystem, including model architectures and fine-tuning approaches - Hands-on experience with: Running LLMs in production: deploying and operating inference workloads LLM fine-tuning, including supervised fine-tuning (SFT/LoRA) and data preparation/curation; experience with RL-based fine-tuning is a strong plus LLM evaluation: building task-specific benchmarks and offline/online eval pipelines, including LLM-as-a-judge setups Inference frameworks and libraries (e.g., vLLM, SGLang, TensorRT-LLM, Transformers) 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 It would be an added bonus if you have: - Experience with inference frameworks and libraries (e.g., vLLM, SGLang, TensorRT-LLM) - Work with multimodal AI models (e.g., vision-language, speech) - Proficiency with DevOps tools (Docker, Kubernetes) - Contributions to open-source ML/AI projects Preferred technical stack: Programming Languages: Python ML Frameworks and Libraries: vLLM, TensorRT-LLM, SGLang, Transformers, OpenAI/Anthropic SDKs MLOps and DevOps tools: Kubernetes (K8s), Docker, Git Cloud Platforms: AWS (SageMaker, Bedrock), GCP (Vertex AI), Azure (Azure ML) Key Employee 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. 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 $210,000 - $260,000 USD 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: Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law. Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire. If you need accommodations during the application process, please let us know.

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