# ML Infrastructure Engineer

**Company**: Nebius
**Location**: Amsterdam
**Work arrangement**: remote
**Experience**: senior
**Job type**: full-time
**Category**: Engineering
**Industry**: Technology

**Apply**: https://job-boards.greenhouse.io/nebius/jobs/4864833101?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/jobs/job_2da7b21b-56e

## Description

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:

- Working closely with hardware and development teams to profile and analyse GPU performance at the system and kernel level.

- Evaluating and comparing GPU performance across different platforms, architectures, and software stacks (e.g., CUDA, ROCm).

- Debugging and optimising ML workloads to run efficiently on GPU hardware, identifying and resolving performance bottlenecks.

- Performing acceptance testing for new GPU clusters, ensuring hardware and software meet performance, stability, and compatibility requirements for AI workloads.

- Performing experiments across diverse GPU system configurations to assess the impact of varying interconnect strategies and system-level optimisations on performance and scalability.

- Developing tools and dashboards to visualise performance metrics, bottlenecks, and trends.

- Contributing 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, TensorRT-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 ownership.

- Collaborative and innovative culture.

- Opportunity to work on impactful AI projects.

- International environment and talented teams.

## Skills

### Required
- machine learning
- AI
- GPU platforms
- deep learning frameworks
- Python
- performance profiling tools
- containerized environments

### Nice to have
- modern LLM inference frameworks
- cloud ML platforms
- open-source ML benchmarking tools

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Source: [Apply at job-boards.greenhouse.io](https://job-boards.greenhouse.io/nebius/jobs/4864833101?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)