Nebius

Nebius

Nebius enables B2B companies to build local hyperscaling cloud platforms with cost-effective GPUs, InfiniBand network, and 50% less compute cost. They offer managed Kubernetes and a launch-ready business model for innovative cloud solutions.

Internet Software & Services
51-250

Description

  • Design, train, and deploy machine learning models for retrieval, reranking, and search relevance in production.
  • Build and optimize 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.
  • Analyze performance trade-offs across latency, quality, and cost.
  • Experiment with state-of-the-art techniques in search, retrieval, and LLM-integrated systems.
  • Contribute to product and architectural decisions in a fast-moving environment.

Requirements

  • 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.
  • Product-oriented mindset with a focus on impact and iteration.
  • Strong problem-solving skills and ability to work in a distributed team.
  • Experience with search systems or large-scale information retrieval is preferred.
  • Familiarity with embeddings, transformers, and modern NLP systems is preferred.
  • Experience working on LLM-powered or agent-based systems is preferred.
  • Contributions to open-source projects, technical publications, or conference talks are preferred.
  • Participation in competitive ML activities such as Kaggle or similar is preferred.

Benefits

  • Competitive salary and comprehensive benefits package.
  • Opportunities for professional growth within Nebius.
  • Flexible working arrangements.
  • A dynamic and collaborative work environment that values initiative and innovation.

Interested in this position?

Apply directly on the company website

Apply Now

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