Machine Learning Engineer

Postaladdress
UK
3 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Working hours
Regular working hours
Job source

Tech stack

Application Programming Interfaces (APIs) Artificial Intelligence C++ (Programming Language) Nvidia CUDA Software Debugging Distributed Systems Python (Programming Language) Machine Learning Open Source Technology Software Deployment Pytorch Large Language Models
+6 more
Model Validation Backend Kubernetes Low Latency Performance Monitor Machine Learning Operations

Job description

As a Senior Machine Learning Engineer, you’ll take the lead on critical projects, guiding the end-to-end lifecycle from research and experimentation to production deployment and performance monitoring. Your work will help shape the capabilities of our platform and enhance the experiences of users who rely on our cutting-edge AI technologies.

What You’ll Be Doing

  • Integrate open-source and third-party models into our inference platform
  • Lead fine-tuning initiatives (LoRA, adapters, PEFT, domain adaptation)
  • Optimise inference workloads for latency, batching, memory efficiency, and throughput
  • Benchmark model quality vs cost vs performance across modalities
  • Improve inference startup times and stability under high load
  • Build evaluation frameworks and internal tooling for model validation
  • Work closely with Infrastructure and Backend teams on scalable serving systems
  • Monitor production performance and drive continuous optimisation
  • Mentor engineers and help raise the ML engineering bar across the team

Requirements

  • Proven experience delivering ML systems to production environments
  • Strong, low-level Python skills and deep hands-on experience with PyTorch
  • Experience working with diffusion models, LLMs, or multimodal architectures
  • Practical experience fine-tuning large models (LoRA, PEFT, adapters, etc.)
  • Experience optimizing inference workloads in GPU environments
  • Strong understanding of model evaluation, experimentation, and monitoring
  • Ability to debug performance, memory, and reliability issues in production
  • Strong systems thinking understanding how ML decisions impact infrastructure
  • High ownership and comfort operating in a fast-paced startup environment

Nice to have

  • Experience with vLLM or custom inference servers
  • Experience with Kubernetes or containerised ML workloads
  • Experience working in high-throughput distributed systems
  • Background in AI media generation (image, video, audio)
  • Experience building internal ML tooling or developer-facing APIs
  • Experience with kernels in CUDA/C++

Benefits & conditions

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 holidays
  • Meaningful stock options - share in the upside you create
  • Remote-first setup - work from home anywhere we can employ you
  • Flexible hours - own your schedule outside core collaboration blocks
  • Family leave - paid maternity, paternity, and caregiver time

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