Manager, ML Solutions Architecture

Job not on LinkedIn

🔥 0 minutes ago

🇺🇸 United States – Remote

💵 $228k - $285k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

💻 Solutions Engineer

👻 Ghost score 20%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Nebius Group

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

🤖 Artificial Intelligence

🏢 Enterprise

☁️ SaaS

Artificial Intelligence • Enterprise • SaaS

Nebius Group is building one of the world’s leading AI infrastructure companies, focusing on providing the necessary compute, storage, and tools for developers in the AI space. Based in Europe and listed on Nasdaq, Nebius has a global presence with R&D centers across Europe, North America, and Israel. The company's primary offering is an AI-centric cloud platform designed for intensive AI workloads, complemented by various other businesses involved in generative AI development, edtech, and autonomous technology.

📋 Description

• Lead a US regional team of 4 Solutions Architects, with continued growth planned • Conduct 1:1s, goal setting, performance reviews, promotion cases, and individual growth plans • Allocate accounts and engagements based on each SA's expertise and interests • Surface blockers early and coordinate with development, product, and business teams to resolve them • Hold team members accountable for delivery outcomes and reflect performance in ratings and compensation decisions • Onboard new joiners through their first independently delivered engagement • Coach Solutions Architects and determine readiness for expanded scope • Own team delivery outcomes, including PoC-to-endpoint time, success-criteria hit rate, and post-production technical relationship quality • Review benchmarking methodology, serving configurations, results, and closure documents before customer delivery • Ensure staffing and escalation coverage across accounts and timezones • Identify infeasibility early with supporting evidence • Maintain and extend documentation, runbooks, guides, onboarding materials, definitions of done, and closure templates • Ensure documentation is used and keep the ticket tracker as the system of record • Define and report delivery speed and reliability metrics • Translate recurring customer pain into prioritized platform work with development and research teams • Manage the scoping-to-execution boundary with pre-sales • Coordinate production handoffs and post-sales technical requests with account management • Report account health, technical feasibility, and capacity needs to business and leadership • Report to the Head of Solutions Architecture and partner with a peer manager in the other region • Deliver PoCs and post-sales technical support for Nebius Token Factory, a serverless platform for running and customizing open-source LLMs in production

🎯 Requirements

• 3+ years managing technical teams, including performance management and difficult conversations • Experience managing a customer-facing team • Strong ML knowledge: LLM architectures, SFT/LoRA/RL-based fine-tuning, evaluation design, inference internals, quantization, KV-cache management, batching, routing, speculative decoding, vLLM, SGLang, and TensorRT-LLM • Technical judgment to review benchmarks and identify methodological flaws • Python strong enough to read and review the team's code • Excellent communication skills for explaining technical concepts to diverse audiences, including enterprise customers under pressure • Tolerance for operational work: documentation, process design, reporting, and follow-through • Comfort operating with ambiguity across distributed teams and timezones • Applicants must be authorized to work in the country in which they apply and provide proof of employment eligibility • Preferred technical stack includes Python; vLLM, TensorRT-LLM, SGLang, Transformers, OpenAI/Anthropic SDKs; Kubernetes, Docker, Git; AWS, GCP, and Azure ML platforms

🏖️ Benefits

• 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