Senior ML Infrastructure Engineer (Research Initiatives) - Systems Integrator

Hamilton Barnes Associates Limited; United Kingdom; Hybrid; GBP 90,000 - 130,000; Full time

Benefits offered by this job

Significant stock option packages

Remote-first working setup

Fully paid travel and accommodation

Full visa sponsorship

Job summary

A leading AI research firm in the UK is seeking a skilled professional to architect AI infrastructure that will redefine engineering through high-speed AI inference. The role includes designing multi-node GPU training environments and collaborating with experts in a vibrant culture. The ideal candidate will be proficient in Kubernetes and experienced in machine learning frameworks. The firm offers competitive equity, a remote-first setup with some in-person presence in London, and full visa sponsorship for top talent.

Qualifications

• Experience designing multi-node/multi-GPU clusters.
• Knowledge of optimization techniques like FSDP and custom kernels.
• Ability to build high-performance pipelines for engineering data.

Responsibilities

• Design and scale training environments using multiple frameworks.
• Manage compute strategies across public and sovereign clouds.
• Implement optimization techniques to maximize performance.
• Integrate physics solvers into machine learning pipelines.
• Setup CI/CD and experiment tracking for validation.

Skills

Expert-level Kubernetes (AKS/EKS)

Strong proficiency in PyTorch

Strong proficiency in JAX

Solid experience with Python

Solid experience with Go

Experience with distributed data tools (Dask/Spark)

Background in AI research labs

Tools

NVIDIA NeMo

OpenFOAM

Simcenter

Job description

Looking to architect next-generation AI infrastructure that transforms engineering simulations?

Join a world-class AI research laboratory, currently in Series B moving to C, that is redefining engineering with Large Physical Models that replace traditional numerical simulations with high-speed AI inference. The role involves building and managing the infrastructure required to train complex simulation models on hundreds of GPUs, leading the orchestration of massive-scale training environments, and contributing to pioneering Physical AI architectures that go far beyond standard generative models. Engineers will work in a high-growth, NVIDIA-backed environment with exposure to cutting-edge AI hardware and sovereign cloud technologies.

Ready to design and scale infrastructure that powers the future of AI-driven engineering? Apply now.

Responsibilities

• Design and scale training environments using PyTorch Distributed, JAX, or NVIDIA NeMo across multi-node/multi-GPU clusters.
• Manage a mixed-compute strategy spanning public clouds (AWS/Azure) and sovereign industrial clouds for sensitive data.
• Implement optimization techniques like FSDP and custom kernels to maximize FLOPS for irregular mesh and 3D geometric data.
• Build high-performance pipelines for ingesting CAE/CFD/FEA engineering data, ensuring zero I/O bottlenecks.
• Integrate traditional physics solvers (OpenFOAM/Simcenter) into ML pipelines for active learning and model refinement.
• Setup \"physics-aware\" CI/CD and experiment tracking (Kubeflow/MLFlow) that validates physical consistency laws.

Skills/Must have

• Orchestration: Expert-level Kubernetes (AKS/EKS) is essential.
• ML Frameworks: Strong proficiency in PyTorch, JAX, or NVIDIA NeMo.
• HPC/Data: Solid experience with Python, Go, and distributed data tools (Dask/Spark).
• Background: Experience in AI research labs (e.g., DeepMind, OpenAI) or Neocloud environments.

Benefits

• Competitive Equity: Significant stock option packages in a fast-scaling Series B/C firm.
• Flexible \"London-Plus\" Setup: Remote-first within Europe/UK, with roughly 1 week per month in London (all travel/accommodation fully paid).
• High-Impact Culture: Work alongside world-renowned physicists, mathematicians, and Formula 1 simulation veterans.
• Sponsorship: Full visa sponsorship available for top-tier global talent.

Salary

• Super Competitive (Base + Bonus + High-Upside Equity)
• Tailored to attract the best in the industry.