Remote opportunity at
NebiusSenior ML Engineer (Agentic Search)
Nebius is a cloud infrastructure provider focused on the global AI economy, delivering a full-stack platform that spans from data training to production deployment. Listed on…
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About This Role
Nebius is a cloud infrastructure provider focused on the global AI economy, delivering a full-stack platform that spans from data training to production deployment. Listed on Nasdaq and headquartered in Amsterdam with an international presence, the company is looking for a Senior ML Engineer to join its expanding team. This position centers on building an agent-native search platform designed for AI systems, helping these systems plan, retrieve, and refine information…
Job Description
Nebius is a cloud infrastructure provider focused on the global AI economy, delivering a full-stack platform that spans from data training to production deployment. Listed on Nasdaq and headquartered in Amsterdam with an international presence, the company is looking for a Senior ML Engineer to join its expanding team. This position centers on building an agent-native search platform designed for AI systems, helping these systems plan, retrieve, and refine information in real time.
This is a remote position where the selected professional will work on production systems operating at web-search scale. The role suits engineers with a product-oriented mindset who want to design models for retrieval, ranking, and indexing, and who excel at balancing system latency, quality, and cost alongside other engineering teams.
Responsibilities
- Train and deploy machine learning models for search relevance, retrieval, and reranking in production environments
- Develop models that assist with content understanding, crawling, and data selection
- Construct and maintain training, data, and evaluation pipelines including retraining and evaluation sets
- Improve machine learning platform infrastructure such as GPU scheduling, experiment tracking, model lifecycle workflows, and low-latency inference optimization
- Collaborate with engineering staff to integrate and launch models into production services
- Implement modern architectural advancements and training methodologies for LLM-integrated and retrieval systems
Requirements
- Minimum of five years of background in applied machine learning or software engineering
- Strong programming abilities in Python along with proficiency in Go or C++
- Demonstrated history of launching machine learning models into production systems
- Sound knowledge of modern deep learning and machine learning concepts, including embeddings and transformers
- Background in building machine learning or data pipelines alongside workflow orchestration experience
- Capability to establish meaningful evaluation metrics and rigorously test models
- Product-oriented mindset emphasizing iteration and impact
Qualifications
- Practical experience with recommendation, ranking, or retrieval
- Familiarity with distributed training, Kubernetes, GPU scheduling, or inference optimization techniques like quantization, batching, and compilation
- Published technical papers, conference talks, or contributions to open-source initiatives
- Demonstrated high performance on public leaderboards or benchmarks, or models published on Hugging Face
Core Skills
Benefits
- Competitive compensation package
- Opportunities for professional growth and learning
- Flexibility and ownership
- Collaborative and innovative working culture
- Involvement in high-impact artificial intelligence projects
- International environment featuring talented teams
Frequently Asked Questions
Answers are based only on the employer’s listing; where it doesn’t say, neither do we.
Is this position remote?
Yes, the source posting specifies that this role is remote.
What is the employment type?
The posting specifies the employment type as full-time.
What salary does Nebius offer for this role?
The salary is not stated in the job posting.
What are the core technical requirements for applicants?
Applicants must have at least five years of software engineering or applied machine learning experience, strong programming skills in Python and either Go or C++, proven production deployment experience, and a solid understanding of modern deep learning, transformers, and embeddings.
Sample Interview Questions
AI-generated questions tailored to this specific role — a preview of the full practice set.