Senior ML Engineer (Agentic Search)

Nebius·Zurichsenior

In short

→Ingeniero ML sénior que construye sistemas de búsqueda inteligentes para IA, con enfoque en recuperación y ranqueo de datos a escala.
→Trabajas día a día con modelos de embeddings, sistemas de indexing y evaluación de calidad en entornos de alta disponibilidad y bajo latencia.
→Destacado: Contribuyes a la capa de acceso web emergente para IA, con impacto directo en cómo las AI acceden a información en tiempo real.

Fluent in English (written and spoken)

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The questions they'll ask you

1. ¿Cómo diseñas un sistema de evaluación de calidad para un modelo de ranqueo en búsqueda con datos de alta variabilidad?

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💵 USD · Remote · No visa

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What they ask for

✓5+ años en ingeniería de software o ML aplicado
✓Dominio en Python, Go o C++
✓Experiencia probada desplegando modelos ML en producción
✓Experiencia en recuperación, ranqueo o recomendaciones
✓Conocimiento sólido en técnicas de ML y deep learning moderno
✓Experiencia con sistemas de datos a gran escala y entornos de alta throughput

Don't tick every box? That's normal — your free dossier shows your gaps and how to cover them in the interview.

PythonGoC++ML modelsembedding-based indexinglarge-scale retrievalretrievalrerankingsearch relevanceevaluation pipelines

Who should you write to at Nebius?

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About Nebius: Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure. Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI. Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D. We are seeking a Senior Applied ML Engineer to join a fast-growing team building an agent-native search platform for AI systems, the emerging web access layer for AI. You will develop and deploy machine learning models that power retrieval, ranking, and indexing at scale, helping AI systems access fresh, reliable information in real time. This is a high-impact role working on a production system used 24x7, tackling challenges comparable to large-scale web search. Your responsibilities: • Design, train, and deploy ML models for retrieval, reranking, and search relevance in production • Build and optimise embedding-based indexing and large-scale retrieval systems • Develop models supporting crawling, data selection, and content understanding • Define and improve quality metrics for agent-native search and build evaluation pipelines • Work on systems operating at very large scale, including high-throughput query workloads • Collaborate closely with engineering teams to integrate ML models into production services • Analyse performance trade-offs across latency, quality, and cost • Experiment with and apply state-of-the-art techniques in search, retrieval, and LLM-integrated systems • Contribute to product and architectural decisions in a fast-moving environment Must-haves: • 5+ years of experience in software engineering or applied machine learning • Strong programming skills in Python, Go, or C++ • Proven experience deploying ML models in production systems • Hands-on experience with retrieval, ranking, recommendation, or similar ML problems • Strong understanding of machine learning and modern deep learning techniques • Experience working with large-scale data systems and high-throughput environments • Ability to design evaluation frameworks and define meaningful model metrics <li

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