Principal ML Solutions Architect – Token Factory

Nebius Group

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

Posted 11/4/2026full-timeRemote • United StatesLead💰 $208,000 - $261,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates extensive expertise in LLM systems, including architecture, fine-tuning, and inference optimization, while effectively leading cross-functional teams to deliver high-impact solutions. Proficient in Python programming and experienced in deploying LLM-powered applications at scale, ensuring performance and reliability.

Highest-signal resume keywords

LLM Ecosystem ExpertiseInference OptimizationPython ProgrammingTechnical LeadershipLLM Fine-Tuning

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

LLM Fine-TuningInference OptimizationModel ArchitecturesQuantizationKV-Cache ManagementBatchingSFT/LoRAData PreparationEvaluation PipelinesTask-Specific LLM Benchmarks

Soft Skills

Excellent CommunicationMentoring

Tools & Technologies

VLLMTensorRT-LLMSGLangOpenAI SDKAnthropic SDKDockerKubernetesAWSGCPAzure ML

Industry Keywords

ML/AI SystemsGenerative AIPrompt EngineeringRAG ArchitecturesProduction-Ready SolutionsCustomer EngagementsTechnical ExecutionOSS ContributionsMultimodal AI ModelsInfrastructure-as-Code

Tech Stack

Tools & technologies

AWSAzureDockerGoogle Cloud PlatformKubernetesPython

About the role

Key responsibilities & impact

Own the most complex, highest-stakes customer engagements from architecture through production across multiple modalities, driving measurable business value
Optimize LLM inference at framework and hardware level and codify best practices into reusable team playbooks
Lead supervised and reinforcement fine-tuning efforts to maximize model quality
Design and implement production-ready LLM solutions using Token Factory inference services
Provide technical expertise in prompt engineering, RAG architectures, model selection, and cost/performance trade-offs at scale
Partner with product, engineering, and research teams to surface customer needs, prototype platform features, and influence the roadmap
Guide customers from proof of concept to production, focusing on performance, reliability, and cost efficiency
Define standards for customer delivery and technical execution
Mentor Senior and mid-level Solutions Architects through review, enablement, and knowledge sharing
Represent Token Factory externally through talks, blog posts, and conferences

Requirements

What you’ll need

8+ years of experience in ML/AI systems, including 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, including model architectures, fine-tuning approaches, and inference internals
Deep, hands-on command of inference optimization, including quantization, KV-cache management, batching, and routing
Experience running LLMs in production at scale, deploying, operating, and debugging inference workloads down to the framework level
Experience with LLM fine-tuning, including SFT/LoRA, data preparation/curation, and RL-based fine-tuning
Experience building task-specific LLM benchmarks and offline/online evaluation pipelines, including LLM-as-a-judge setups
Experience with inference frameworks and libraries such as vLLM, SGLang, and TensorRT-LLM, including reading, modifying, and contributing to their internals
Experience deploying LLM-powered applications using OpenAI, Anthropic, or open-source model APIs
Strong Python programming skills
Excellent communication skills, with ability to explain technical concepts to engineers and executives
Applicants must be authorized to work in the country in which they apply and provide proof of employment eligibility
Added bonus: contributions or maintainership in major OSS inference/ML projects
Added bonus: published research, conference talks, or widely-read technical writing in the LLM/serving space
Added bonus: deep work with multimodal AI models
Added bonus: proficiency with Docker, Kubernetes, and infrastructure-as-code
Added bonus: experience building or owning internal ML workflow tooling/automation at scale
Preferred technical stack includes Python; vLLM, TensorRT-LLM, SGLang, Transformers, OpenAI/Anthropic SDKs; Kubernetes, Docker, Git; AWS, GCP, and Azure ML platforms

Benefits

Comp & perks

100% company-paid medical, dental, and vision coverage for employees and families
401(k) plan with up to 4% company match and immediate vesting
20 weeks paid parental leave for primary caregivers and 12 weeks for secondary caregivers
Up to $85/month remote work reimbursement for mobile and internet
Company-paid short-term, long-term, and life insurance coverage
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