高级应用机器学习工程师（代理搜索）
Senior Applied ML Engineer (Agentic Search)
关于Nebius：
Nebius正在引领全球AI经济的云基础设施新时代。我们正在构建一个全栈AI云平台，支持开发者和企业从数据和模型训练到生产部署，无需承担构建大型内部AI/ML基础设施的成本和复杂性。
由工程师打造，面向工程师。从大规模GPU编排到推理优化，我们在计算、存储、网络和应用AI领域掌握着最困难的问题。
在纳斯达克上市（NBIS），总部位于阿姆斯特丹，我们拥有遍布欧洲、英国、北美和以色列的全球研发中心。我们的团队超过1500人，包括数百名在硬件、软件和AI研发方面具有深厚专业知识的工程师。
我们正在寻找一位高级应用机器学习工程师加入一个快速发展的团队，该团队正在构建一个原生代理搜索平台，用于AI系统，这是新兴的AI网络访问层。您将开发和部署机器学习模型，以支持大规模的检索、排序和索引，帮助AI系统实时访问新鲜可靠的信息。这是一个高影响力的角色，涉及24x7运行的生产系统，解决的挑战与大规模网络搜索相当。
您的职责：
- 在生产环境中设计、训练并部署用于检索、重新排序和搜索相关性的机器学习模型
- 构建和优化基于嵌入的索引和大规模检索系统
- 开发支持爬取、数据选择和内容理解的模型
- 定义并改进原生代理搜索的质量指标，并构建评估流程
- 从事大规模系统工作，包括高吞吐量查询工作负载
- 与工程团队紧密合作，将机器学习模型集成到生产服务中
- 分析延迟、质量和成本之间的性能权衡
- 尝试并应用搜索、检索和LLM集成系统中的最先进技术
- 在快速变化的环境中为产品和架构决策做出贡献
必备条件：
- 5年以上软件工程或应用机器学习经验
- 精通Python、Go或C++编程
- 有在生产系统中部署机器学习模型的经验
- 有处理检索、排序、推荐或类似机器学习问题的实际经验
- 对机器学习和现代深度学习技术有深刻理解
- 有使用大规模数据系统和高吞吐量环境的经验
查看英文原文
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
- Product-oriented mindset with a focus on impact and iteration
- Strong problem-solving skills and ability to work in a distributed team
Nice-to-haves:
- Experience with search systems or large-scale information retrieval
- Familiarity with embeddings, transformers, and modern NLP systems
- Experience working on LLM-powered or agent-based systems
- Contributions to open-source projects, technical publications, or conference talks
- Participation in competitive ML (e.g. Kaggle) or similar signals of strong technical ability
We conduct coding interviews as part of the process.
Benefits & Perks:
- 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
What's it like to work at Nebius:
Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI
Equal Opportunity Statement:
Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law.
Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire.
If you need accommodations during the application process, please let us know.