Senior ML Engineer – AI Research, Portability

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🔥 0 minutes ago

🌐 Netherlands, United Kingdom – Remote

🇳🇱 Netherlands – Remote 🇬🇧 United Kingdom – Remote

⏰ Full Time

🟠 Senior

🤖 AI Engineer

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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

• Design and build research prototypes and robust systems at the seams between models, providers, and agent runtimes • Formulate research questions and develop evaluation methods • Test ideas in realistic agent workflows and turn promising results into reusable components • Research model routing, provider and protocol portability, agent interoperability, portable memory and context, agent interchange standards, and agent optimization • Design, implement, train, and evaluate model routers • Develop portable provider and protocol abstractions preserving authentication, telemetry, cache and context signals, and execution provenance • Define versioned schemas and contracts for models, providers, agents, workspaces, skills, actions, tools, memories, and trajectories • Build systems to discover, package, adapt, and validate agent skills across coding agents, editors, and other harnesses • Research user-owned memory, scoped identity, trajectory checkpoints, retrieval quality, and context compaction • Create benchmark suites and evaluation protocols for quality, cost, latency, reliability, safety, and portability • Conduct held-out, out-of-domain, and change-impact evaluations • Investigate distillation, self-improving harnesses, multi-agent training, agent factories, and automated skill creation • Write robust research software, APIs, integration layers, and reproducible test infrastructure • Collaborate across research, infrastructure, security, product, and engineering teams • Communicate results through technical reports, demonstrations, open-source releases, benchmarks, and research publications

🎯 Requirements

• Profound understanding of machine learning, large language models, or statistical decision-making • Deep expertise in at least one relevant area, such as model routing, recommender systems, agent systems, retrieval and memory, model evaluation, distributed systems, or protocol and API design • Experience building and evaluating modern language-model or agentic systems, including tool use and multi-turn workflows • Experience designing, executing, and analyzing machine learning experiments with appropriate statistical rigor • Ability to formulate meaningful research questions, design hypothesis-driven experiments, and draw defensible conclusions • Understanding of evaluation leakage, held-out testing, out-of-domain generalization, uncertainty, and reproducibility • Strong software-engineering and algorithm-design skills • Excellent Python skills and ability to work across production systems • Experience with APIs, data schemas, distributed services, testing, observability, code review, and CI/CD • Ability to reason about security, privacy, provenance, permissions, failure modes, and user control in agent systems • Experience implementing research ideas across modeling, data, systems, and evaluation • Strong communication and technical leadership abilities • Nice-to-have experience with model routers, cascades, mixture-of-experts systems, recommenders, or cost-aware inference • Nice-to-have experience integrating multiple model providers or inference stacks • Nice-to-have familiarity with agent harnesses, coding agents, editor integrations, function calling, tool execution, MCP, or agent-to-agent protocols • Nice-to-have experience with retrieval systems, vector search, knowledge graphs, temporal data, memory architectures, or context management • Nice-to-have experience with benchmark suites, distillation, reinforcement learning, preference learning, reward modeling, automated skill generation, secure authentication, sandboxing, privacy-preserving telemetry, provenance, policy-enforced execution, and distributed systems • Nice-to-have proficiency in TypeScript, Go, Rust, or another systems language in addition to Python • Nice-to-have PhD in Computer Science, Machine Learning, Artificial Intelligence, or a related technical field, or equivalent practical experience • Excellent command of English, with strong technical writing, presentation, and communication skills • Proficiency in version control, testing, code review, and CI/CD

🏖️ 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 • Fast moving • Bold thinking • Constant growth • Meaningful impact • Trust and real ownership • Opportunity to shape the future of AI • Equal employment opportunities • Accommodations during the application process