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PhysicsX

Principal Machine Learning Infrastructure Engineer

PhysicsX · London, United Kingdom

Posted about 2 months ago

or apply directly on PhysicsX's site. We never take the application ourselves.

Is this posting real?

This role has been open
66 days
PhysicsX's roles stay open a median of 66 days
Reposted
No
Salary listed
No
26% of PhysicsX's roles list one
Ghost-job risk at PhysicsX
high
33 stale, 2 reposted of 42 open
Hiring momentum
58 roles opened in the last 90 days
↑ up vs. the prior 90 days
Last confirmed on the employer's board
2026-10-08

Measured from postings appearing on and disappearing from PhysicsX's own greenhouse board since 2026-08-03. Full hiring picture for PhysicsX.

About this role

The Principal Machine Learning Infrastructure Engineer at PhysicsX will be responsible for extending and operating the infrastructure that supports research model training and serving pipelines. This role involves collaborating closely with ML engineers and research scientists to optimize training infrastructure, manage data pipelines, and ensure reliable model serving. The engineer will also have end-to-end responsibilities for research infrastructure, making architectural decisions and improving the developer experience for the research team.

Our read on this posting3.2out of 5
benefits
5/5
freshness
1/5
career value
5/5
role clarity
5/5
pay transparency
0/5

Scored from the posting itself — how clearly the role is described, how much it says about pay and benefits, and how recently it was listed. Not a judgement of PhysicsX as an employer.

What you need

  • 5+ years of experience building and operating ML infrastructure at scale
  • Deep expertise in distributed training
  • Strong systems fundamentals: Linux, networking, storage I/O, profiling and performance optimization
  • Production experience with Kubernetes and SLURM for job orchestration on GPU clusters
  • Proficiency in Python and ML frameworks (PyTorch strongly preferred)
  • Experience with cloud GPU infrastructure

Nice to have

  • Experience with geometric deep learning or neural operators
  • Background in HPC for simulation engineering
  • Experience building model serving infrastructure with latency and throughput requirements
  • Familiarity with experiment tracking tools and observability stacks
  • Experience packaging models for deployment into customer environments

What you get

  • Equity options
  • 10% employer pension contribution
  • Free office lunches
  • Enhanced parental leave
  • YellowNest nursery scheme
  • 25 days of Annual Leave (+ Public Holidays)

Worth weighing

  • No salary listed
  • The role requires deep expertise in distributed training, which may limit candidates without this experience
  • Collaboration with research scientists may require strong communication skills in technical contexts
  • The position involves a flat structure, which may not suit everyone

Summarised from PhysicsX's posting. Read the full original.

Listed by PhysicsX on their greenhouse job board, last confirmed open on 2026-10-08. PitchMeAI is not the employer.

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