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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 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.

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. Key employee benefits in the US: Health insurance: 100% company-paid medical, dental, and vision coverage for employees and families. 401(k) plan: Up to 4% company match with immediate vesting. Parental leave: 20 weeks paid for primary caregivers, 12 weeks for secondary caregivers. Remote work reimbursement: Up to $85/month for mobile and internet. Disability & life insurance : Company-paid short-term, long-term and life insurance coverage. Pay Transparency We offer competitive compensation and benefits packages. Actual compensation will be determined based on job-related factors, including experience, skills, qualifications, the level at which the candidate is hired, and geographic location, consistent with applicable law. Base Compensation Range $195,200 — $262,200 USD 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 Product Token Factory is focused on building a next-generation platform that enables companies to seamlessly integrate AI into their products and workflows. Our vision is to create a powerful, open, and scalable alternative for deploying and managing AI systems—making advanced AI infrastructure more accessible to both fast-growing startups and large enterprises. We work with a wide range of customers, from AI-first companies to established technology organisations, helping them run AI workloads reliably at scale. Our goal is to become a leading platform for high-performance AI inference, delivering predictable latency, strong reliability, and the ability to scale to meet demanding production needs. Customer feedback plays a central role in how we build—our development process is highly iterative and closely aligned with real-world use cases. About the Team We are a fast-growing, distributed team of engineers and product professionals based primarily in Europe. The team brings together strong backend, frontend, product, and business expertise, with a shared focus on building impactful, scalable systems. While we initially started without deep specialisation in AI/ML, the team has rapidly grown into the space—demonstrating strong ownership, curiosity, and the ability to tackle complex technical challenges. Technology & Environment Our work is deeply integrated with a broader cloud and infrastructure ecosystem. We primarily use Go and Python to build and scale backend systems and collaborate closely with teams focused on areas such as infrastructure, observability, billing, and AI research. The platform continues to evolve from a lightweight integration layer into a more comprehensive system, including custom infrastructure, optimisations, and deeper control over performance and reliability. What We’re Working On Scaling distributed systems: Expanding our platform to handle significantly increased workloads while maintaining performance and reliability Improving reliability: Enhancing system stability and uptime to meet enterprise-grade expectations Optimising AI performance: Continuously adapting to new models, hardware, and runtime improvements Expanding platform capabilities: Building beyond inference into broader AI infrastructure, including data pipelines, customization, and advanced usage features We expect you to have: 5+ years of professional software development experience. Strong software engineering skills (we mostly use Python and Go). Proficiency in contemporary software engineering approaches, including CI/CD, version control and unit testing. Experience with developing web services. A commitment to maintaining extreme rigor in all job-related activities. Nice to have: Previous experience working with language models or other similar NLP technologies. A track record of building and delivering products (not necessarily ML-related) in a dynamic startup-like environment. Strong engineering skills, including experience in developing large distributed systems or high-load web services. Open-source projects that showcase your engineering prowess. Why It’s Interesting This is an opportunity to work at the intersection of distributed systems, cloud infrastructure, and applied AI , tackling real-world scalability challenges and shaping how companies adopt AI in production environments. 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 Product Token Factory is focused on building a next-generation platform that enables companies to seamlessly integrate AI into their products and workflows. Our vision is to create a powerful, open, and scalable alternative for deploying and managing AI systems—making advanced AI infrastructure more accessible to both fast-growing startups and large enterprises. We work with a wide range of customers, from AI-first companies to established technology organisations, helping them run AI workloads reliably at scale. Our goal is to become a leading platform for high-performance AI inference, delivering predictable latency, strong reliability, and the ability to scale to meet demanding production needs. Customer feedback plays a central role in how we build—our development process is highly iterative and closely aligned with real-world use cases. About the Team We are a fast-growing, distributed team of engineers and product professionals based primarily in Europe. The team brings together strong backend, frontend, product, and business expertise, with a shared focus on building impactful, scalable systems. While we initially started without deep specialisation in AI/ML, the team has rapidly grown into the space—demonstrating strong ownership, curiosity, and the ability to tackle complex technical challenges. Technology & Environment Our work is deeply integrated with a broader cloud and infrastructure ecosystem. We primarily use Go and Python to build and scale backend systems and collaborate closely with teams focused on areas such as infrastructure, observability, billing, and AI research. The platform continues to evolve from a lightweight integration layer into a more comprehensive system, including custom infrastructure, optimisations, and deeper control over performance and reliability. What We’re Working On Scaling distributed systems: Expanding our platform to handle significantly increased workloads while maintaining performance and reliability Improving reliability: Enhancing system stability and uptime to meet enterprise-grade expectations Optimising AI performance: Continuously adapting to new models, hardware, and runtime improvements Expanding platform capabilities: Building beyond inference into broader AI infrastructure, including data pipelines, customization, and advanced usage features We expect you to have: 5+ years of professional software development experience. Strong software engineering skills (we mostly use Python and Go). Proficiency in contemporary software engineering approaches, including CI/CD, version control and unit testing. Experience with developing web services. A commitment to maintaining extreme rigor in all job-related activities. Nice to have: Previous experience working with language models or other similar NLP technologies. A track record of building and delivering products (not necessarily ML-related) in a dynamic startup-like environment. Strong engineering skills, including experience in developing large distributed systems or high-load web services. Open-source projects that showcase your engineering prowess. Why It’s Interesting This is an opportunity to work at the intersection of distributed systems, cloud infrastructure, and applied AI , tackling real-world scalability challenges and shaping how companies adopt AI in production environments. 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 Token Factory is a part of Nebius Cloud, one of the world’s largest GPU clouds, running tens of thousands of GPUs. We are building an inference & fine-tuning platform that makes every kind of foundation model — text, vision, audio, and emerging multimodal architectures — fast, reliable, and effortless to train & deploy at massive scale. Some directions we currently working on and which you can be a part of: Advanced Fine-Tuning: Enhancing fine-tuning methodologies - both LoRA-based and full-parameter - for cutting-edge LLMs (e.g., GPT-OSS, Kimi K2.5, DeepSeek V3.1/V3.2, GLM-4.7), focusing on both model quality and training efficiency. Inference Optimization: Identifying LLM inference bottlenecks to drive production speedups. This involves building model training and evaluation pipelines in JAX for speculative decoding, experimenting with architectures (dense/MoE, auto-regressive/parallel), and deriving scaling laws to guide resource allocation. Low Precision Training & Inference: Investigating low-precision (FP8, NVFP4/MXFP4) methodologies for supervised fine-tuning and reinforcement learning - spanning both inference and training - optimized for modern hardware We expect you to have: A profound understanding of theoretical foundations of machine learning and reinforcement learning. Deep expertise in modern deep learning for language processing and generation Experience with training large models on multiple computational nodes Reasonable understanding of performance aspects of large neural network training (sharding strategies, custom kernels, hardware features etc.) Strong software engineering skills (we mostly use Python) Deep experience with modern deep learning frameworks (we use JAX) Proficiency in contemporary software engineering approaches, including CI/CD, version control and unit testing Strong communication and leadership abilities Nice to have: Previous experience working with language models or other similar NLP technologies. Familiarity with important ideas in LLM space, such as MHA, RoPE, ZeRO/FSDP, Flash Attention, quantization A track record of building and delivering products (not necessarily ML-related) in a dynamic startup-like environment. Strong engineering skills, including experience in developing large distributed systems or high-load web services. Open-source projects that showcase your engineering prowess Excellent command of the English language, alongside superior writing, articulation, and communication skills. 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.