ML Infrastructure Engineer

Nebius; Amsterdam (VA); On-site; USD 130,000 - 190,000; Full time

Benefits offered by this job

Competitive compensation

Career growth and learning

Flexibility and ownership

Collaborative and innovative culture

Impactful AI projects

Job summary

Nebius is building a full-stack AI cloud platform and seeks a highly skilled ML/AI Engineer to lead benchmarking of GPU platforms for ML workloads. You will evaluate GPU performance across platforms and frameworks and help drive platform optimisation and future hardware development.

You will profile at system and kernel levels, debug ML workloads, and develop dashboards to visualise performance trends. Collaboration with hardware, software, and cloud teams is essential.

Qualifications

• Benchmark GPU platforms for ML workloads and AI frameworks.
• Profile and analyse GPU performance at system/kernel level.
• Debug and optimise ML workloads on GPU hardware.

Responsibilities

• Profile GPU performance across platforms and architectures.
• Evaluate CUDA/ROCm performance for AI workloads.
• Develop tools/dashboards to visualize performance trends.
• Perform acceptance testing for GPU clusters for AI workloads.
• Collaborate with hardware and software teams for optimisation.
• Contribute to internal tooling and best practices.

Skills

GPU benchmarking

Performance profiling

PyTorch

JAX

Megatron-LM

Tensor-LLM

Tools

Nsight

nvprof

Docker

Kubernetes

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.

The role

We are seeking a highly skilled ML/AI Engineer to join our team to lead and support 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 and 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 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, bottlenecks, and trends.
• Contribute to internal tooling, frameworks, and best practices.

We Expect You To Have

• A profound understanding of the 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 containerised 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 ownership.
• Collaborative and innovative culture.
• Opportunity to work on impactful AI projects.
• International environment and talented teams.

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.