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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. The Product In a rapidly evolving world, trust in AI depends on AI agents being grounded in fresh, verified real-world data. Search is the foundation that makes this possible. We are building an agent-native search platform designed specifically for AI systems rather than human users. Our product provides programmatic, low-latency, and observable search APIs that AI agents use to retrieve, filter, and reason over real-world information at scale. The Role As a Senior ML Engineer focused on Search Optimization, you will work on improving the quality of our search product across the all parts of the search stack. You will work on problems such as query understanding, query reformulation and expansion, retrieval, ranking, reranking, and result selection. Your goal will be to identify where search quality is lost, develop better approaches, and turn them into measurable improvements in production. This is an applied ML and information-retrieval role combining experimentation with production impact. You will work with real-world queries, large-scale search systems, and evaluation signals to improve relevance, recall, freshness, and overall result quality. In this position, your responsibility will be to Design, implement, and operate the retrieval system for a search vertical Connect and tune the data pipeline, from ingestion to relevance tuning Build knowledge-graph and entity-resolution layers: entity linking / NER , ontologies, and graph databases (Neo4j or similar) Develop structured-extraction pipelines over messy, unstructured domain data Reason about freshness and trust: model how confident we are in a fact and how stale it has become before we serve it Define evaluation and quality metrics for relevance and drive measurable improvements Collaborate with crawling, indexing, and ML teams to ensure retrieval and ranking requirements are met Enable safe experimentation with retrieval, ranking, and extraction strategies You may be a good fit if you have: 6+ years of software engineering experience, some of it in search / information retrieval Strong IR fundamentals: inverted indexes, BM25 / TF-IDF , query understanding, ranking, and evaluation (nDCG/ MRR /recall@k) Experience with vector & hybrid retrieval: ANN, dense+sparse fusion, embeddings models Experience building structured extraction over messy/unstructured domain data Fluent in Python and comfortable with systems-level performance work Strong candidates may also have experience with: Knowledge graphs: entity resolution, entity linking / NER , graph DBs (Neo4j), ontologies / schema design Owning relevance / ranking for a real product and improving it against IR metrics Data quality, truth discovery, or systems that decide how much to trust a piece of information Published work on IR , ranking, or knowledge graphs 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.

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. About the Role We are looking for a technically strong, hands-on QA Engineer to join our hardware team on-site at ODM factories in Taiwan. This is not a checklist job - we're looking for someone who enjoys digging deep into technical issues, investigating root causes, and taking ownership of complex hardware problems.You'll be the key person ensuring the quality of our servers and racks before they ship, but more importantly, you'll play a critical role in debugging failures, analyzing test data, and working closely with RnD, logistics, and factory teams to continuously improve the process and the product.This is a deeply technical role that blends hardware validation, manufacturing QA, and problem-solving - perfect for someone who understands how servers are built and tested, and wants to make sure every unit that leaves the factory is production-grade. What You'll Own Technical Investigation & Debugging Investigate complex problems (e.g., high GPU failure rate, power-related test failures), gather logs, run diagnostics, and escalate with context to RnD when needed. Drive root cause analysis across factory teams and internal engineering groups. Document findings and help define preventive actions for recurring problems. Act as the first line of technical escalation for hardware issues discovered during factory QA or internal testing.Engineering Support Participate in new platform bring-up sessions together with the visiting RnD teams during on-site trips to ODM labs. Provide technical support, coordination, and hands-on assistance during the bring-up process. Help ensure early-stage hardware behaves as expected, and escalate integration or platform issues to the relevant teams.On-Site Product QA Perform visual inspections of completed products (servers, racks) before packaging. Define and maintain QA checklists and inspection procedures tailored to different product lines. Verify inventory records at the factory against internal system data (part numbers, serials, configurations). Oversee the product packaging process for compliance with defined standards. Supervise pickup operations: ensure outbound trucks meet shipment conditions and schedules.Failure Rate Monitoring & Analytics Collect failure data from vendor-side burn-in and our own test systems. Analyze failure trends and estimate spare part needs for future datacenter deployments. Use dashboards and structured reporting to communicate insights with QA, engineering, and supply chain teams.Feedback Loop & Quality Improvement Gather and process feedback from datacenters on each delivered batch of equipment: * Report on packaging issues, impact sensor triggers, shipping anomalies. * Assess rack-level build quality: cabling, bracket alignment, labeling. * Log systemic hardware issues (design flaws, infant mortality, recurring failures). Forward the feedback to the teams: logistics, ODM partners, hardware RnD, QA.Test Infrastructure & Validation Assist with deployment and maintenance of test infrastructure on-site. Ensure Nebius post-manufacturing hardware validation tests run smoothly (uptime, monitoring, coordination with support team). Coordinate real-time issue escalation and basic triage with factory and internal teams.Local Insight & Communication Communicate relevant local risks and context (e.g., typhoons, holidays, factory-specific constraints) to our global logistics and hardware teams. Maintain productive relationships with factory staff, logistics providers, and internal stakeholders. Working Conditions & Tools During production peaks, issues may arise that require fast, hands-on debugging and resolution on-site. Flexibility is expected: you may need to stay late to investigate failures in freshly built batches or arrive early to verify and unblock outbound truck shipments. Rapid response and clear communication with engineering and factory teams are critical during these high-pressure periods. Occasional international travel may be expected to Nebius headquarters in Amsterdam or to datacenters in Europe and the US. Daily work tools involve: * Managing workflows and escalation via Jira * Writing and maintaining technical documentation in Confluence * Using Grafana dashboards for monitoring test environments and system health * Operating with several internal inventory and test control systems What You'll Bring Strong technical background in hardware or systems engineering, able to independently investigate and troubleshoot complex issues with server systems. 5+ years of experience in hardware QA, manufacturing supervision, or server validation. A strong background in R&D is a significant plus. Solid understanding of server and rack hardware: components, layout, cabling, power/cooling, diagnostics. Ability to read and interpret technical documentation (e.g., datasheets, system specs, debug manuals). Solid knowledge of electrical engineering fundamentals (e.g., power specs, grounding, signal integrity). 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.

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 looking for a Senior Software Engineer to work on the core search application powering our agentic search platform. In this role, you will build and operate a high-scale, latency-sensitive API that sits at the center of the search request flow. The system orchestrates multiple retrieval capabilities, ranking components, and downstream services to serve thousands of search requests per second while balancing search quality, latency, reliability, and infrastructure cost. In this position, your responsibility will be to Design, implement, and operate core backend components of a search orchestration system, spanning online services and background data pipelines. Build well-tested services and pipelines with clear responsibilities and interaction contracts, while remaining flexible as the system evolves Define and implement observability primitives, including structured logs, metrics, traces, and quality signals for both online and offline components Support experimentation and iteration by enabling feature flags, controlled rollouts, and online experiments Track throughput, latency, and resource usage across the system, and improve performance or cost efficiency when business needs require it Collaborate closely with ML engineers to integrate search quality improvements to the system, while keeping ML logic decoupled from core system internals Monitor resource usage, bandwidth consumption, and infrastructure cost Work with data analysts and product managers to translate product and quality goals into concrete backend behavior and measurable metrics You may be a good fit if you: 5+ years of experience building product critical backend services Strong Go and Python Experience Experience with large-scale distributed systems (5k+ RPS, billions of events, high-throughput pipelines) Understanding of Information Retrieval flows and pipelines Experience operating production systems and debugging failures in distributed environments Strong understanding of scalability, fault tolerance, and resource management Are interested in either a strong senior IC role or a role with significant technical leadership and ownership. 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.

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. About Tavily We're building the infrastructure layer for agentic web interaction at scale. Our API is designed from the ground up to power Retrieval-Augmented Generation (RAG) and real-time reasoning in AI systems. By connecting LLMs to high-quality, trustworthy web content, we help developers build agents that are not only intelligent — but also informed. We work with some of the most innovative teams in AI — from small startups shaping the ecosystem to the largest enterprises deploying AI at scale. Whether it's powering sales assistants, research copilots, or internal knowledge tools, we're the missing link between LLMs and the real world. The Role: Senior Site Reliability Engineer Managing Kubernetes clusters across multiple environments and regions Owning infrastructure as code for all resources Maintaining and improving CI/CD pipelines and GitOps-based deployments Maintaining and optimize real-time data pipelines that process billions of events per day across distributed queues and stream processors Building out monitoring, alerting, and observability Debugging production issues across services Managing cloud costs and capacity planning Working closely with a small engineering team — you'd own infra, not a slice of it What we're looking for 3+ years in a DevOps or platform engineering role, working in production environments Proven experience designing and operating large-scale, distributed systems, with a solid understanding of API design, reliability, and performance at scale Strong Kubernetes experience in a managed cloud environment Proficiency with infrastructure as code (Terraform or similar) Experience with GitOps-based deployment workflows Built or maintained observability stacks (logging, metrics, alerting) Experience handling production incidents calmly and methodically Nice to have: Multi-region deployments Search infrastructure Data pipeline experience (streaming, warehousing) Proxy/networking infrastructure at scale Why Tavily? Full ownership — small team, you own the entire infrastructure, not a slice of it Real scaling challenges — bursty scraping workloads, cache invalidation, multi-region, millions of daily requests AI-native company — your infra directly powers AI agents used by leading companies in the space. 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.

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. The role Nebius Token Factory needs scientists who can turn frontier inference bottlenecks into research problems, publish credible work, and then help ship the results into production. This is not a papers-only research role. The Applied Scientist is expected to design rigorous experiments, write strong code, collaborate with engineers, and convert research into deployed inference capabilities. A Senior Applied Scientist owns well-scoped research and production optimization projects. They can publish or prepare high-quality technical work while also producing code, experiments, and prototypes that engineers can use. Your responsibilities : Own focused research projects from hypothesis through experiment, ablation, prototype, and production handoff. Prepare internal reports, technical blogs, or papers when the work is externally credible. Partner directly with MLEs to ensure research prototypes become usable production components. Define and execute research programs in efficient LLM and VLM inference with measurable production impact. Invent, evaluate, and productionize methods for quantization, QAT , distillation, speculative decoding, KV -cache reuse, KV -cache compression, long-context inference, MoE routing, and model/runtime co-optimization. Build high-quality prototypes in PyTorch, Triton, CUDA -adjacent tooling, or inference-serving frameworks, then work with MLEs and platform engineers to productionize them. Design rigorous evaluation methodology covering quality, latency, throughput, numerical stability, memory footprint, tail latency, and cost per token. Publish papers, technical reports, blog posts, and open-source artifacts that build external credibility for Nebius Token Factory. Collaborate with MLE, GPU kernel, backend infrastructure, product, and customer teams to choose high-leverage research bets. Mentor engineers and scientists on experimental design, scientific rigor, and model/system tradeoffs. Must-haves : PhD in computer science, machine learning, ML systems, computer systems, computer architecture, electrical engineering, applied math, or a closely related field. Strong publication record or equivalent research artifacts in ML, ML systems, efficient inference, model compression, quantization, distillation, serving systems, or related areas. Strong hands-on coding ability in Python and PyTorch; ability to move from idea to experiment to prototype quickly. Deep understanding of LLMs, VLMs, transformer inference, decoding algorithms, model compression, quantization, and production-serving tradeoffs. Strong experimental design skills, including ablations, baselines, metrics, statistical reasoning, and failure analysis. Excellent written and verbal communication. Nice - to - have s : First-author publications in NeurIPS, ICML , ICLR , MLSys, ACL , EMNLP , ASPLOS , OSDI , SOSP , ISCA , HPCA , or comparable venues. Experience deploying ML models or inference optimizations in production. Experience with vLLM, SGLang, TensorRT-LLM, NVIDIA Dynamo, FlashAttention, FlashInfer, Triton, CUDA , or PyTorch internals. Experience with post-training, SFT , DPO , RLHF , RLAIF , preference optimization, or synthetic data generation when connected to inference quality or efficiency. Open-source research artifacts, widely used benchmarks, high-quality technical blogs, or invited talks in efficient AI systems. 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.

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. The role Nebius Token Factory needs scientists who can turn frontier inference bottlenecks into research problems, publish credible work, and then help ship the results into production. This is not a papers-only research role. The Applied Scientist is expected to design rigorous experiments, write strong code, collaborate with engineers, and convert research into deployed inference capabilities. A Senior Applied Scientist owns well-scoped research and production optimization projects. They can publish or prepare high-quality technical work while also producing code, experiments, and prototypes that engineers can use. Your responsibilities : Own focused research projects from hypothesis through experiment, ablation, prototype, and production handoff. Prepare internal reports, technical blogs, or papers when the work is externally credible. Partner directly with MLEs to ensure research prototypes become usable production components. Define and execute research programs in efficient LLM and VLM inference with measurable production impact. Invent, evaluate, and productionize methods for quantization, QAT , distillation, speculative decoding, KV -cache reuse, KV -cache compression, long-context inference, MoE routing, and model/runtime co-optimization. Build high-quality prototypes in PyTorch, Triton, CUDA -adjacent tooling, or inference-serving frameworks, then work with MLEs and platform engineers to productionize them. Design rigorous evaluation methodology covering quality, latency, throughput, numerical stability, memory footprint, tail latency, and cost per token. Publish papers, technical reports, blog posts, and open-source artifacts that build external credibility for Nebius Token Factory. Collaborate with MLE, GPU kernel, backend infrastructure, product, and customer teams to choose high-leverage research bets. Mentor engineers and scientists on experimental design, scientific rigor, and model/system tradeoffs. Must-haves : PhD in computer science, machine learning, ML systems, computer systems, computer architecture, electrical engineering, applied math, or a closely related field. Strong publication record or equivalent research artifacts in ML, ML systems, efficient inference, model compression, quantization, distillation, serving systems, or related areas. Strong hands-on coding ability in Python and PyTorch; ability to move from idea to experiment to prototype quickly. Deep understanding of LLMs, VLMs, transformer inference, decoding algorithms, model compression, quantization, and production-serving tradeoffs. Strong experimental design skills, including ablations, baselines, metrics, statistical reasoning, and failure analysis. Excellent written and verbal communication. Nice - to - have s : First-author publications in NeurIPS, ICML , ICLR , MLSys, ACL , EMNLP , ASPLOS , OSDI , SOSP , ISCA , HPCA , or comparable venues. Experience deploying ML models or inference optimizations in production. Experience with vLLM, SGLang, TensorRT-LLM, NVIDIA Dynamo, FlashAttention, FlashInfer, Triton, CUDA , or PyTorch internals. Experience with post-training, SFT , DPO , RLHF , RLAIF , preference optimization, or synthetic data generation when connected to inference quality or efficiency. Open-source research artifacts, widely used benchmarks, high-quality technical blogs, or invited talks in efficient AI systems. 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.

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. The role Nebius Token Factory needs scientists who can turn frontier inference bottlenecks into research problems, publish credible work, and then help ship the results into production. This is not a papers-only research role. The Applied Scientist is expected to design rigorous experiments, write strong code, collaborate with engineers, and convert research into deployed inference capabilities. A Senior Applied Scientist owns well-scoped research and production optimization projects. They can publish or prepare high-quality technical work while also producing code, experiments, and prototypes that engineers can use. Your responsibilities : Own focused research projects from hypothesis through experiment, ablation, prototype, and production handoff. Prepare internal reports, technical blogs, or papers when the work is externally credible. Partner directly with MLEs to ensure research prototypes become usable production components. Define and execute research programs in efficient LLM and VLM inference with measurable production impact. Invent, evaluate, and productionize methods for quantization, QAT , distillation, speculative decoding, KV -cache reuse, KV -cache compression, long-context inference, MoE routing, and model/runtime co-optimization. Build high-quality prototypes in PyTorch, Triton, CUDA -adjacent tooling, or inference-serving frameworks, then work with MLEs and platform engineers to productionize them. Design rigorous evaluation methodology covering quality, latency, throughput, numerical stability, memory footprint, tail latency, and cost per token. Publish papers, technical reports, blog posts, and open-source artifacts that build external credibility for Nebius Token Factory. Collaborate with MLE, GPU kernel, backend infrastructure, product, and customer teams to choose high-leverage research bets. Mentor engineers and scientists on experimental design, scientific rigor, and model/system tradeoffs. Must-haves : PhD in computer science, machine learning, ML systems, computer systems, computer architecture, electrical engineering, applied math, or a closely related field. Strong publication record or equivalent research artifacts in ML, ML systems, efficient inference, model compression, quantization, distillation, serving systems, or related areas. Strong hands-on coding ability in Python and PyTorch; ability to move from idea to experiment to prototype quickly. Deep understanding of LLMs, VLMs, transformer inference, decoding algorithms, model compression, quantization, and production-serving tradeoffs. Strong experimental design skills, including ablations, baselines, metrics, statistical reasoning, and failure analysis. Excellent written and verbal communication. Nice - to - have s : First-author publications in NeurIPS, ICML , ICLR , MLSys, ACL , EMNLP , ASPLOS , OSDI , SOSP , ISCA , HPCA , or comparable venues. Experience deploying ML models or inference optimizations in production. Experience with vLLM, SGLang, TensorRT-LLM, NVIDIA Dynamo, FlashAttention, FlashInfer, Triton, CUDA , or PyTorch internals. Experience with post-training, SFT , DPO , RLHF , RLAIF , preference optimization, or synthetic data generation when connected to inference quality or efficiency. Open-source research artifacts, widely used benchmarks, high-quality technical blogs, or invited talks in efficient AI systems. 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.

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. The role Nebius Token Factory needs scientists who can turn frontier inference bottlenecks into research problems, publish credible work, and then help ship the results into production. This is not a papers-only research role. The Applied Scientist is expected to design rigorous experiments, write strong code, collaborate with engineers, and convert research into deployed inference capabilities. A Senior Applied Scientist owns well-scoped research and production optimization projects. They can publish or prepare high-quality technical work while also producing code, experiments, and prototypes that engineers can use. Your responsibilities : Own focused research projects from hypothesis through experiment, ablation, prototype, and production handoff. Prepare internal reports, technical blogs, or papers when the work is externally credible. Partner directly with MLEs to ensure research prototypes become usable production components. Define and execute research programs in efficient LLM and VLM inference with measurable production impact. Invent, evaluate, and productionize methods for quantization, QAT , distillation, speculative decoding, KV -cache reuse, KV -cache compression, long-context inference, MoE routing, and model/runtime co-optimization. Build high-quality prototypes in PyTorch, Triton, CUDA -adjacent tooling, or inference-serving frameworks, then work with MLEs and platform engineers to productionize them. Design rigorous evaluation methodology covering quality, latency, throughput, numerical stability, memory footprint, tail latency, and cost per token. Publish papers, technical reports, blog posts, and open-source artifacts that build external credibility for Nebius Token Factory. Collaborate with MLE, GPU kernel, backend infrastructure, product, and customer teams to choose high-leverage research bets. Mentor engineers and scientists on experimental design, scientific rigor, and model/system tradeoffs. Must-haves : PhD in computer science, machine learning, ML systems, computer systems, computer architecture, electrical engineering, applied math, or a closely related field. Strong publication record or equivalent research artifacts in ML, ML systems, efficient inference, model compression, quantization, distillation, serving systems, or related areas. Strong hands-on coding ability in Python and PyTorch; ability to move from idea to experiment to prototype quickly. Deep understanding of LLMs, VLMs, transformer inference, decoding algorithms, model compression, quantization, and production-serving tradeoffs. Strong experimental design skills, including ablations, baselines, metrics, statistical reasoning, and failure analysis. Excellent written and verbal communication. Nice - to - have s : First-author publications in NeurIPS, ICML , ICLR , MLSys, ACL , EMNLP , ASPLOS , OSDI , SOSP , ISCA , HPCA , or comparable venues. Experience deploying ML models or inference optimizations in production. Experience with vLLM, SGLang, TensorRT-LLM, NVIDIA Dynamo, FlashAttention, FlashInfer, Triton, CUDA , or PyTorch internals. Experience with post-training, SFT , DPO , RLHF , RLAIF , preference optimization, or synthetic data generation when connected to inference quality or efficiency. Open-source research artifacts, widely used benchmarks, high-quality technical blogs, or invited talks in efficient AI systems. 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.