11 hours ago
Remote, EMEA +3 moreSenior
Responsibilities
- Design, train, and deploy production ML models for retrieval, reranking, search relevance, crawling, data selection, and content understanding.
- Build and optimize embedding-based indexing and large-scale retrieval systems for high-throughput workloads.
- Define quality metrics and build evaluation pipelines for agent-native search.
- Integrate ML models into production services and analyze latency, quality, and cost trade-offs.
- Apply state-of-the-art search, retrieval, and LLM-integrated techniques while contributing to product and architecture decisions.
Requirements
- At least 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 machine learning problems.
- Strong understanding of machine learning and modern deep learning techniques.
- Experience with large-scale data systems and high-throughput environments.
- Ability to design evaluation frameworks and define meaningful model metrics.
- Preferred qualifications include search or large-scale information retrieval experience, familiarity with embeddings, transformers, and modern NLP systems, experience with LLM-powered or agent-based systems, open-source or publication contributions, and competitive ML experience such as Kaggle.
- Coding interviews are part of the hiring process.
Benefits
- Competitive compensation.
- Career growth and learning opportunities.
- Flexibility, ownership, and an opportunity to work on impactful AI projects.
- Collaborative, innovative, and international environment with talented teams.
Categories
About Nebius
Nebius builds a full-stack AI cloud offering GPU compute, storage, and tools for training and deploying ML models for startups, enterprises, and research labs. It sells consumption-based cloud infrastructure (IaaS/PaaS) and managed services tailored to generative AI workloads, including large-scale model training and inference. The company is headquartered in Amsterdam and operates as an independent provider.