<div class="show-more-less-html__markup show-more-less-html__markup--clamp-after-5 relative overflow-hidden"> We're looking for a Senior Machine Learning Engineer to own and scale the AI systems behind Bolt Food's merchant catalogue and opportunity sizing systems, spanning LLM-based enrichment and categorisation through to fine-tuned open-weight models we train and serve ourselves, all in service of automating merchant operations across 50+ markets.<br/><br/><strong>About Us<br/><br/></strong>With over 200 million customers across 50+ countries and 850+ cities, Bolt is one of the fastest-growing tech companies in Europe and Africa — powered by 4.5+ million partners on our platform, 4,000+ employees globally. And it's all thanks to our people.<br/><br/>We believe in creating an inclusive environment where everyone is welcome, regardless of race, colour, religion, gender identity, sexual orientation, national origin, age, or ability.<br/><br/>Our ultimate goal is to make cities for people, not cars — and we need your help on this mission!<br/><br/><strong>About The Role<br/><br/></strong>You'll join the Delivery Merchant engineering group alongside software engineers, product managers, and data scientists who build the systems our merchant partners depend on. Your mission is to make our ML-powered catalogue automation substantially better by raising model quality, hardening services into reliable production systems, and extending into new areas like agentic catalogue workflows and merchant scoring.<br/><br/>There's also a significant frontier here. Today we rely heavily on third-party API models. You'll help drive our transition to fine-tuned open-weight models we own and serve ourselves, giving us better economics, lower latency, and more control. This is early-stage, high-leverage work where you'll shape the technical direction.<br/><br/>This is a hybrid, end-to-end role. You'll work from ambiguous business problems through offline evaluation, online experiments, and production systems, and you'll stay accountable for the outcomes.<br/><br/><strong>Main Tasks And Responsibilities<br/><br/></strong><ul><li>Design, train, and deploy ML/LLM models that automate catalogue enrichment, moderation, and categorisation at scale, owning accuracy, latency, and cost in production.</li><li>Drive the transition from frontier API models to fine-tuned open-weight models: build data curation and fine-tuning pipelines, run quality comparisons, and take winners into production.</li><li>Design and build agentic AI systems for catalogue automation, covering multi-step workflows, tool use, guardrails, and the evaluation harnesses to prove they work.</li><li>Build evaluation and experimentation infrastructure: offline benchmarks, regression suites, LLM-as-judge pipelines, and A/B tests tied to business metrics.</li><li>Own the serving and cost story for self-hosted models, including quantisation, throughput tuning, GPU utilisation, and build-versus-buy decisions.</li><li>Collaborate cross-functionally with Software Engineers, Data Scientists, Product Managers, and the ML Platform team to productionise and monitor ML solutions.<br/><br/></li></ul><strong>About You<br/><br/></strong><ul><li>Proven experience building and shipping ML systems in production at scale, ideally in consumer-facing product environments at a technology company.</li><li>Demonstrated track record taking LLM-based systems to production, including prompt/model iteration, evaluation, guardrails, observability, and cost management.</li><li>Hands-on experience fine-tuning and serving open-weight models (e.g. LoRA/QLoRA, SFT, preference optimisation), including building training data and managing production serving.</li><li>Deep expertise in NLP or recommendation systems, with models that have moved a business metric.</li><li>Strong engineering fundamentals: mastery of Python and SQL, clean code practices, production experience with a deep learning framework (PyTorch, TensorFlow, JAX, or Triton), and experience with modern ML tooling and cloud infrastructure (AWS, SageMaker, Airflow, Docker).</li><li>Strong product sense and proactive ownership, with the ability to turn ambiguous problems into measurable ML solutions and drive them from discovery to production impact.<br/><br/></li></ul>Experience is great, but what we really look for is drive, intelligence, and integrity. So even if you don't tick every box, please consider applying!<br/><br/><strong>Why you'll love it here<br/><br/></strong><ul><li>Play a direct role in shaping the future of mobility.</li><li>Make an impact on millions of customers and partners across 850+ cities in 50+ countries.</li><li>Work in fast-moving, autonomous teams with talented and supportive colleagues.</li><li>Accelerate your professional growth with unique career opportunities.</li><li>Receive a rewarding salary and stock option package that lets you focus on doing your best work.</li><li>Enjoy the flexibility of hybrid working, with a minimum of 3 days in the office each week to foster strong connections and teamwork.</li><li>Take care of your physical and mental health with our wellness perks.<br/><br/></li></ul><em>Some perks may differ depending on your location and role.<br/><br/></em> </div>