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# Senior Machine Learning Engineer

- **Company:** Unitedkingdom
- **Location:** UK (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Nvidia CUDA, Software Debugging, Python (Programming Language), Machine Learning, Large Language Models, Model Validation, Backend, Kubernetes, Machine Learning Operations
- **Published:** September 13, 2026
- **Apply:** https://www.apply4u.co.uk/jobs/senior-machine-learning-engineer/47106442

## About the Role

inference serversExperience with Kubernetes or containerised ML workloadsExperience working in high-throughput distributed systemsBackground in AI media generation (image, video, audio)Experience building internal ML tooling or developer-facing APIsExperience with kernels in CUDA/C++We're a remote-first team that comes together in person twice a year to plan, collaborate, and celebrate wins. Day to day we keep a few core hours for teamwork, but outside of that you set the schedule that helps you do your best work.Our environment is fast-moving and ambitious. Big pushes are part of building category-defining products, but we balance that with flexible working, generous time off, and regular retreats so the team can stay sharp and motivated.Generous paid time off- vacation, sick days, public holidaysMeaningful stock options- share in the upside you createRemote-first setup- work from home anywhere we can employ youFlexible hours- own your schedule outside core collaboration blocksFamily
leave- paid maternity, paternity, and caregiver timeCompany retreats- twice-yearly gatherings in inspiring locations #J-18808-Ljbffr

## Description

high loadBuild evaluation frameworks and internal tooling for model validationWork closely with Infrastructure and Backend teams on scalable serving systemsMonitor production performance and drive continuous optimisationMentor engineers and help raise the ML engineering bar across the teamWhat We're Looking ForProven experience delivering ML systems to production environmentsStrong, low-level Python skills and deep hands-on experience with PyTorchExperience working with diffusion models, LLMs, or multimodal architecturesPractical experience fine-tuning large models (LoRA, PEFT, adapters, etc.)Experience optimizing inference workloads in GPU environmentsStrong understanding of model evaluation, experimentation, and monitoringAbility to debug performance, memory, and reliability issues in productionStrong systems thinking understanding how ML decisions impact infrastructureHigh ownership and comfort operating in a fast-paced startup environmentNice to haveExperience with vLLM or custom


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