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Senior Machine Learning Software Engineer, Research

PhysicsX· Research
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Hybrid (London, United Kingdom)full-timePosted 5mo ago

About the role

Senior-level ML software engineer focused on building and optimizing the end-to-end ML training stack and model architectures for physics AI applications, with an emphasis on scalable training, efficient inference, and research-to-production pipelines.

Responsibilities

  • Own the training stack end to end: experiment harness, sweeps, distributed training, checkpointing, and throughput.
  • Implement and optimise model architectures with efficiency perspective: sparse attention and convolution, custom kernels, memory and precision work, and making a prototype fast enough to train at scale.
  • Take architectural ideas from prototype to trained model, and own the ablations that establish whether a change actually helped.
  • Set technical direction for the training stack, and build the inference and evaluation path that turns a checkpoint into something usable.
  • Identify engineering investments that unlock research progress.

Qualifications

  • Senior-level experience in training machine learning models at scale, in industry or a research group of comparable intensity, instrumental in: distributed training with FSDP or equivalent, including profiling and diagnosing idle GPUs; PyTorch and CUDA at depth, ideally including sparse convolution or sparse attention internals and custom CUDA or Triton kernels; implementing architectures from papers and making them work, then making them fast; reproducible experiment infrastructure.
  • Experience with 3D or other irregular data: meshes, point clouds, voxels, sparse tensors.
  • Ability to scope and deliver projects, and strong problem-solving skills.
  • Degree in CS, engineering, mathematics, physics or a related field. A PhD is welcome but not required; engineering depth matters more.

Skills

Required:Distributed training with FSDP or equivalentPyTorch and CUDA internalsArchitectural implementation from papersReproducible experiment infrastructure3D or irregular data handling

Benefits

  • Equity options
  • 10% employer pension contribution
  • Free office lunches
  • Enhanced parental leave - 3 months full pay paternity and 6 months full pay maternity leave
  • YellowNest nursery scheme
  • 25 days of Annual Leave (+ Public Holidays)
  • Private medical insurance - 100% employee cover
  • Wellhub Subscription
  • Eye tests
  • Personal development support
  • Employee Assistance Programme (EAP)
  • Bike2Work scheme and Season ticket loan
  • Octopus EV salary sacrifice
Last updated Sep 23, 2026. Interested? Apply on the company site.

About PhysicsX

Accelerating Industrial Innovation with AI

PhysicsX is deploying AI to transform how physical systems are engineered, embedding intelligence across the entire product lifecycle, from concepting and design to manufacturing and operations.

AIIndustrial InnovationDesignManufacturingOperationsAI ToolsProduct Lifecycle
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