<div class="show-more-less-html__markup show-more-less-html__markup--clamp-after-5 relative overflow-hidden"> <p><strong>Machine Learning Engineer</strong></p><p><strong>Remote Europe | Up to €150,000 + Equity</strong></p><p><br/></p><p>I am working with a well backed AI startup building infrastructure for the next generation of production AI systems.</p><p><br/></p><p>They are solving a very real problem in the AI market. Companies are using large general purpose LLMs in production, but for repeatable tasks these models can be expensive, slow and difficult to control.</p><p><br/></p><p>This team is building a platform that trains smaller, task specific language models that can match frontier model quality on narrow tasks, while reducing cost and latency.</p><p>They are backed by one of Europe’s leading AI investors and already work with customers across defence, cybersecurity, robotics and education.</p><p><br/></p><p>Why this one stands out</p><ul><li>Up to €150,000 plus equity</li><li>Remote across European time zones</li><li>Early team, real ownership and strong career progression</li><li>Backed by one of Europe’s leading AI investors</li><li>Working on a fundamental AI infrastructure problem</li><li>Building systems around small language models, synthetic data, fine tuning, evaluation and inference</li><li>Regular team offsites in Europe</li></ul><p><br/></p><p><strong>The Role</strong></p><p><br/></p><p>This is a hands on Machine Learning Engineer role sitting across ML infrastructure, model training, backend systems and low latency inference.</p><p>You will help build the full production pipeline behind task specific language models, from synthetic data generation and fine tuning through to evaluation, serving, monitoring and deployment.</p><p>It is not a pure research role and it is not a pure backend role. The strongest fit will be someone who can build real ML systems around models and understands how to take them into production.</p><p><br/></p><p><strong>What you will work on</strong></p><p><br/></p><p>Build and improve infrastructure for synthetic data generation, model training and evaluation</p><p>Work on scalable orchestration for GPU jobs using Kubernetes, Argo Workflows or similar</p><p>Run and optimise fine tuning workloads using PyTorch, Hugging Face, LoRA, DDP, FSDP or similar</p><p>Build high throughput teacher model inference pipelines</p><p>Develop validation and filtering systems to keep synthetic training data high quality</p><p>Build secure, multi tenant model serving infrastructure for production workloads</p><p>Work on low latency inference, auto scaling, observability and cost monitoring</p><p>Partner closely with ML scientists on knowledge distillation, synthetic data generation and model evaluation</p><p>Help turn research into reliable customer facing systems</p><p><br/></p><p><strong>What they are looking for</strong></p><ul><li>Strong Python engineering skills</li><li>Experience building ML, data or backend infrastructure at scale</li><li>Hands on experience with model training, fine tuning or distributed ML workloads</li><li>Experience with PyTorch, Hugging Face, JAX, TensorFlow or similar</li><li>Good understanding of Kubernetes, workflow orchestration or distributed compute</li><li>Experience with Docker, cloud infrastructure and infrastructure as code</li><li>Exposure to model serving, inference optimisation or production ML systems</li><li>Strong problem solving skills and a bias towards automation and reliability</li><li>Comfortable working in a small, fast moving technical team</li></ul><p><br/></p><p><br/></p><p><strong>Who this could suit</strong></p><p>This could suit someone from an ML infrastructure, ML platform, LLM infrastructure, research engineering or applied ML engineering background.</p><p>You might be someone who has worked across training, evaluation, serving and deployment, and now wants more ownership in a smaller, highly technical AI company.</p><p>The strongest fit will be someone who enjoys building real systems around models and cares about making AI cheaper, faster and reliable enough for production.</p><p><br/></p><p><strong>The practicalities</strong></p><ul><li>Remote across European time zones</li><li>Regular team offsites in Europe</li><li>Up to €150,000 plus equity</li><li>Early team with strong technical ownership</li><li>Backed by one of Europe’s leading AI investors</li></ul> </div>