Machine Learning Engineer LLM
<p><b>Salary: £100,000 - 100,000 per year</b></p>
<b>Requirements:</b>
<ul><li>Strong experience with training deep learning models in production</li><li>In-depth knowledge of PyTorch with hands-on experience in torch.distributed (DDP/FSDP-style training)</li><li>Experience of training large sequence models or LLMs at scale</li><li>Software engineering background with Python; familiarity with TypeScript and/or Golang</li><li>Distributed systems/training ops experience with practical knowledge of multi-node jobs on GPU clusters (Slurm, Kubernetes, or managed cloud equivalents)</li><li>Familiarity with GPU performance tuning (memory usage, mixed precision, throughput vs. latency trade-offs)</li><li>Experience within a reinforcement learning environment</li><li>Collaborative with great communication skills</li><li>Degree educated to BSc/MSc in a relevant discipline</li></ul>
<b>Responsibilities:</b>
<ul><li>Take open-source LLMs and convert them into high-performance software engineer agents using supervised fine-tuning and large-scale reinforcement learning</li><li>Design and run extensive training experiments across multi-node GPU clusters</li><li>Build RL loops where models write code and receive feedback based on real test outcomes</li><li>Push long-context and MoE style architectures to their limits</li><li>Work hands-on across the full stack including custom PyTorch dataloaders, distributed training, and debugging NCCL issues</li><li>Design opinionated reward functions that reflect exceptional engineering practices</li><li>Extend benchmark suites and test models on real-world repositories</li><li>Analyze failure modes and provide insights to improve data and training strategies</li><li>Collaborate with infrastructure, product, and research teams to inform training decisions and result measurements</li></ul>
<b>Technologies:</b>
<ul><li>AI</li><li>Cloud</li><li>Golang</li><li>Kubernetes</li><li>Machine Learning</li><li>PyTorch</li><li>Python</li><li>TypeScript</li><li>NodeJS</li><li>LLM</li></ul>
<p><b>More:</b></p>
<p>We are a London-based tech start-up with £5 million in recent pre-seed funding, focused on creating an impactful AI agentic platform that writes production-grade code. We offer a dog-friendly office environment with daily catered lunches, 30 days of holiday (including bank holidays), salary up to £110k, equity options, pension, and monthly socials. Our working hours are from 0900-1700, with no expectation to work beyond these hours. We are looking for a Machine Learning Engineer who can shape and influence our product.</p>
<p>last updated 8 week of 2026</p>
<b>Requirements:</b>
<ul><li>Strong experience with training deep learning models in production</li><li>In-depth knowledge of PyTorch with hands-on experience in torch.distributed (DDP/FSDP-style training)</li><li>Experience of training large sequence models or LLMs at scale</li><li>Software engineering background with Python; familiarity with TypeScript and/or Golang</li><li>Distributed systems/training ops experience with practical knowledge of multi-node jobs on GPU clusters (Slurm, Kubernetes, or managed cloud equivalents)</li><li>Familiarity with GPU performance tuning (memory usage, mixed precision, throughput vs. latency trade-offs)</li><li>Experience within a reinforcement learning environment</li><li>Collaborative with great communication skills</li><li>Degree educated to BSc/MSc in a relevant discipline</li></ul>
<b>Responsibilities:</b>
<ul><li>Take open-source LLMs and convert them into high-performance software engineer agents using supervised fine-tuning and large-scale reinforcement learning</li><li>Design and run extensive training experiments across multi-node GPU clusters</li><li>Build RL loops where models write code and receive feedback based on real test outcomes</li><li>Push long-context and MoE style architectures to their limits</li><li>Work hands-on across the full stack including custom PyTorch dataloaders, distributed training, and debugging NCCL issues</li><li>Design opinionated reward functions that reflect exceptional engineering practices</li><li>Extend benchmark suites and test models on real-world repositories</li><li>Analyze failure modes and provide insights to improve data and training strategies</li><li>Collaborate with infrastructure, product, and research teams to inform training decisions and result measurements</li></ul>
<b>Technologies:</b>
<ul><li>AI</li><li>Cloud</li><li>Golang</li><li>Kubernetes</li><li>Machine Learning</li><li>PyTorch</li><li>Python</li><li>TypeScript</li><li>NodeJS</li><li>LLM</li></ul>
<p><b>More:</b></p>
<p>We are a London-based tech start-up with £5 million in recent pre-seed funding, focused on creating an impactful AI agentic platform that writes production-grade code. We offer a dog-friendly office environment with daily catered lunches, 30 days of holiday (including bank holidays), salary up to £110k, equity options, pension, and monthly socials. Our working hours are from 0900-1700, with no expectation to work beyond these hours. We are looking for a Machine Learning Engineer who can shape and influence our product.</p>
<p>last updated 8 week of 2026</p>