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PhysicsX is the physics AI company for industrials. The company’s mission is to accelerate hardware innovation by overhauling what industrial engineering and manufacturing look like today. PhysicsX is building a new simulation software stack to deliver deep physics AI enablement across the entire engineering lifecycle. The company partners with leading organisations in aerospace & defence, automotive, semiconductors, materials, and energy & renewables, supporting them on some of their most critical and complex challenges. PhysicsX is headquartered in the United Kingdom, with offices in London, New York, and Singapore and an expanding presence in the Bay Area.
Our Research team runs large-scale training jobs and data generation workflows for CAE and LPM training on an HPC cluster comprising of 304 B200s, orchestrated via SLURM on Kubernetes. We’re looking for a Senior Infrastructure Engineer to help us build, scale, and operate this platform - and to work directly with researchers to keep their jobs running fast, safely, and reliably.
This role is split roughly evenly between platform engineering (building, hardening, and optimising the infrastructure everything runs on), and hands-on support (debugging job failures, optimising throughput, and helping Research get the most out of the cluster).
What you will do- Design, build, and maintain our SLURM-on-Kubernetes infrastructure, supporting large-scale distributed training and data generation workloads
- Own cluster reliability, efficiency, and utilization across hundreds of GPUs
- Partner directly with the Research team to debug job failures, diagnose performance bottlenecks, and improve iteration speed
- Build and maintain containerized job job environments (Docker, Enroot/Pyxis) for reproducible research workflows
- Manage high-performance storage systems to support data-intensive CAE workloads
- Develop tooling, automation, and observability to reduce operational overhead and catch issues before they impact the Research team
- Contribute to capacity planning and infrastructure roadmap as the cluster and team scale
- Build and implement a technical and scaling strategy for Research’s use of high-performance computing to achieve efficient large-scale model training and data generation workloads
- 4-6 years of experience in infrastructure, platform, or HPC engineering roles
- Hands-on experience with SLURM and Kubernetes, ideally running them together in production environments
- Experience with containerization and orchestration for compute-heavy workloads (Docker, Enroot/Pyxis, etc)
- Working knowledge of high-performance networking (Infiniband, RDMA, NCCL) in the context of distributed training
- Experience managing HPC/ML storage systems at scale
- Strong debugging skills across the stack - from scheduling and networking to individual job failures
- Comfortable working directly with researchers and translating their needs into infrastructure improvements
- Solid scripting/automation skills
- Experience operating GPU clusters at scale (hundreds of GPUs or more)
- Background in CAE or simulation-driven data generation
- Experience with GPU cluster health monitoring and fault tolerance for long-running training jobs
- Familiarity with infrastructure-as-code tools (Terraform, Helm, etc)
Build what actually matters
Help shape an AI-native engineering company at a formative stage, tackling problems that genuinely matter for industry and society. This is work with real-world impact - and something you can be proud to stand behind.
Learn alongside exceptional people
Work with a high-caliber, collaborative team of engineers, scientists, and operators who care deeply about doing great work, and about helping each other get better. We come from diverse backgrounds, but we share a commitment to operating at the highest level and addressing some of the most complex challenges out there. If you’re ambitious, thoughtful, and driven by impact, you’ll feel at home.
Influence over hierarchy
We operate with a flat structure: good ideas win - wherever they come from. Questioning assumptions and challenging the status quo isn’t just welcomed, it’s expected.
Sustainable pace, long-term ambition
Building meaningful technology is a marathon, not a sprint. We believe in balancing focused, ambitious work with a life beyond it. Our hybrid model blends time together in our Shoreditch office with work-from-home days, giving you the flexibility to work sustainably while staying connected in person.
Skills Required
- 5+ years building and operating ML infrastructure at scale
- Deep expertise in distributed training and collective communication (NCCL, FSDP vs DDP vs pipeline parallelism)
- Strong systems fundamentals: Linux, networking (including NVLink and InfiniBand), storage I/O, profiling and performance optimization
- Production experience with Kubernetes and SLURM for GPU cluster job orchestration
- Proficiency in Python and ML frameworks (PyTorch strongly preferred)
- Experience with cloud GPU/HPC infrastructure (e.g., CoreWeave or similar)
- Ability to scope and deliver projects, prioritise work, and troubleshoot complex issues
- Excellent collaboration and communication skills in a research setting
- Experience with geometric deep learning or neural operators (meshes, point clouds, graphs)
- Background in HPC for simulation engineering and familiarity with CFD/FEA data workflows
- Experience building model serving infrastructure addressing latency and throughput constraints
- Familiarity with experiment tracking and observability tools (Weights & Biases, MLflow, Prometheus, Grafana)
- Experience packaging models for customer deployment (containers, model registries, versioning)
- Experience with NVIDIA DGX platforms
What We Do
PhysicsX is a deep-tech company of scientists and engineers, developing machine learning applications to accelerate physics simulations and enable a new frontier of optimization opportunities in design and engineering. Born out of numerical physics, we help our customers radically improve their concepts and designs, transform their engineering processes and drive operational product performance. We do this in some of the most advanced and important industries of our time – including Space, Aerospace, Medical Devices, Additive Manufacturing, Electric Vehicles, Motorsport, and Renewables. Our work creates positive impact for society, be it by improving the design of artificial hearts, reducing CO2 emissions from aircraft and road vehicles, and increasing the performance of wind turbines. We are currently recruiting for multiple positions, however please only apply for the role that best aligns with your skillset and career goals. We do not currently offer work experience
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