Machine Learning Engineer PyTorch LLM

London, Greater London | £80k - £110k per year

Do you have expertise with Machine Learning in production? You could be progressing your career at a London based tech start-up with £5 million in recent pre‑seed funding, in an impactful role that you'll shape. The product is an AI agentic based platform that writes production‑grade code.

What's in it for you:

• Salary to £110k
• Equity / stock options
• 30 days holiday (plus Bank Holidays)
• Daily lunch, monthly breakfasts
• Dog friendly office
• Pension
• Monthly socials
• Impactful role that you can shape and influence

Your role:

As a Machine Learning Engineer you'll take open-source LLMs (code and general models) and turn them into high-performance software engineer agents using supervised fine‑tuning and large‑scale reinforcement learning. This isn't prompt engineering. You'll design and run serious training experiments across multi‑node GPU clusters, build RL loops where models write code and get rewarded (or penalised) by real test outcomes and push long‑context and MoE style architectures to their limits. You'll work hands‑on across the full stack: custom PyTorch dataloaders, distributed training (DDP/FSDP), experiment tracking, debugging NCCL issues at 2 am, and squeezing performance out of multi‑GPU jobs. You'll help design opinionated reward functions that reflect what great engineering actually looks like, not just benchmark scores. You'll extend benchmark suites, test models on real‑world repositories, analyse failure modes and feed insights back into data and training strategy. Collaborating with infrastructure, product and research teams you'll contribute to decisions about what to train next and how to measure results.

Location / WFH:

You'll be based in the London, dog‑friendly office on a full‑time basis, with daily catered lunch, working hours 0900‑1700 (with no expectation to do more).

About you:

• You have strong experience with training deep learning models in production
• You have an indepth knowledge of PyTorch including hands‑on experience with torch.distributed (DDP/FSDP‑style training, distributed data loading, gradient scaling, etc.)
• You have experience of training large sequence models or LLMs at scale
• You have a software engineering background with Python, also familiar with TypeScript and / or Golang
• You have distributed systems / training ops experience including practical experience running multi‑node jobs on GPU clusters (Slurm, Kubernetes, or managed cloud equivalents) and are familiar with GPU performance tuning: memory usage, mixed precision, throughput vs. latency trade‑offs
• You have experience within a reinforcement learning environment
• You're collaborative with great communication skills
• You are degree educated to BSc / MSc in a relevant discipline

Apply now or call to find out more about this Machine Learning Engineer opportunity.