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ML Infrastructure Engineer

Nebius Group

Role overview

Qualifications

  • Profound understanding of the theoretical foundations of machine learning
  • Deep experience with performance aspects of large neural networks training and inference (data/tensor/context/expert parallelism, offloading, custom kernels, hardware features, attention optimisations, dynamic batching)
  • Deep experience with modern deep learning frameworks (PyTorch, JAX, Megatron-LM, Tensort-LLM)
  • Familiarity with containerized environments (Docker, Kubernetes)

Responsibilities

  • Profile and analyse GPU performance at the system and kernel level in collaboration with hardware and development teams
  • Evaluate and compare GPU performance across different platforms, architectures, and software stacks (CUDA, ROCm)
  • Debug and optimise ML workloads to run efficiently on GPU hardware, identifying and resolving performance bottlenecks
  • Perform experiments across diverse GPU configurations to assess the impact of interconnect strategies and system-level optimisations on performance and scalability

About the company

Nebius Group logo

Nebius Group

Cloud Computing & Infrastructure (IaaS/PaaS)

Nebius Group is building one of the largest commercially available AI infrastructure businesses, based in Europe. Our core business is an AI-centric cloud platform built for intensive AI workloads. We are building full-stack infrastructure to service the explosive growth of the global AI industry, including large-scale GPU clusters, cloud platforms and tools and services for developers. Our headquarters and main R&D presence is in Amsterdam, with additional R&D and commercial hubs in Europe, North America and Israel. Our businesses operate and serve customers on four continents. Our name reflects our mission and values as a company. Combining nebula, the Latin word for cloud, with a reference to the endless Möbius strip, the name Nebius embodies our belief in the endless possibilities offered by cloud technologies. In addition to our core AI infrastructure business, we are developing three other businesses that operate under their own distinctive individual brands: • Toloka AI – a data partner for all stages of AI development from training to evaluation; • TripleTen – a leading edtech player in the US and certain other markets, re-skilling people for careers in tech; • Avride – one of the most experienced teams developing autonomous driving technology for self-driving cars and delivery robots. The group is led by Arkady Volozh, the entrepreneur and visionary co-founder of Yandex.

Company details

IndustryCloud Computing & Infrastructure (IaaS/PaaS)
Company size1001 - 5000

Links

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Job description

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

We are seeking a highly skilled ML/AI Engineer to join our team to lead and support benchmarking of GPU platforms benchmarking of GPU platforms for machine learning and AI workloads. You will play a critical role in evaluating the performance of GPU-based hardware for various deep learning and AI frameworks, enabling data-driven decisions for platform optimisation and next-generation hardware development.

Your responsibilities will include:

  • Work closely with hardware, development teams to profile and analyse GPU performance at the system and kernel level.
  • Evaluate and compare GPU performance across different platforms, architectures, and software stacks (e.g.,CUDA, ROCm).
  • Debug and optimise ML workloads to run efficiently on GPU hardware, identifying and resolving performance bottlenecks.
  • Perform acceptance testing acceptance testing for new GPU clusters, ensuring hardware and software meet performance, stability, and compatibility requirements for AI workloads.
  • Perform experiments across diverse GPU system configurations to assess the impact of varying interconnect strategies and system-level optimisations on performance and scalability.
  • Develop tools and dashboards to visualise performance metrics visualise performance metrics, bottlenecks, and trends.
  • Contribute to internal tooling, frameworks, and best practices

We expect you to have:

  • A profound understanding of theoretical foundations of machine learning
  • Deep understanding of performance aspects of large neural networks training and inference (data/tensor/context/expert parallelism, offloading, custom kernels, hardware features, attention optimisations, dynamic batching etc.)
  • Deep experience with modern deep learning frameworks (PyTorch, JAX, Megatron-LM, Tensort-LLM)
  • Good understanding of the GPU stack: CUDA,NCCL, drivers, and relevant libraries
  • Familiarity with containerized environments (e.g., Docker, Kubernetes).
  • Strong communication and ability to work independently

 

Ways to stand out from the crowd:

  • Familiarity with modern LLM inference frameworks (vLLM, SGLang, TensorRT)
  • Experience in Python and performance profiling tools (e.g., Nsight, nvprof, perf).
  • Familiarity with cloud ML platforms like AWS, GCP, Azure ML
  • Contributions to open-source ML benchmarking tools

Benefits & Perks:

  • Competitive compensation
  • Career growth and learning opportunities
  • Flexibility and work-life balance
  • 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.

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Marcus Rivera

Chief Revenue Officer

m.rivera@company.com
linkedin.com/in/marcusrivera
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