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Lead Machine Learning Engineer | SNAP Team at ZOE. Location Information: UK,Europe. We Are Redefining How People Approach Their Health. ZOE. is the science and nutrition company leading a movement to transform the health of millions.. We exist because the food we eat is making us sick. Most of what we are taught about food is wrong.. ZOE runs the world’s largest nutrition science study to find scientifically proven solutions.. Our randomised controlled trial of ZOE proves that if you eat the right food for your body, you can feel healthier in weeks and be on track for more healthy years.. ZOE can change the way you eat, feel, and live. We host world-leading scientists on our podcast and bring proven science to your plate with Daily30+, our 30+ plant supplement.. Over 100,000 people rely on ZOE Membership, our personalised nutrition program, to make smarter food choices. ZOE Membership turns complex science into clear step-by-step actions, helping you improve your health with every meal.. ZOE means life — and you can change your life with food.. Visit our . career page. and become a ZOEntist 🚀. 👥 The Team. At . ZOE. , we're on a mission to empower people with the most advanced science and technology to transform their health. Our . Snap. team is at the heart of this mission, developing AI-driven solutions that make food logging effortless—just by using a camera! If you're passionate about cutting-edge machine learning, building impactful products, and solving real-world problems, this is the role for you.. 🚀 . The Role. We are seeking a . Lead Machine Learning Engineer. to join our dynamic ML Engineering team. In this pivotal role, you will be instrumental in scaling our AI-driven photo logging product to millions of users, tackling a diverse range of complex technical challenges from inception to production. You’ll work on architecting, designing, and maintaining the highly performant and reliable ML systems that power our core product.. You'll lead by example, mentoring junior engineers, driving technical discussions, and collaborating closely with cross-functional teams including product managers, data scientists, software engineers, and UX designers to deliver a best-in-class customer experience.. 🎯 What You’ll Be Doing. Lead the end-to-end development and scaling. of our core photo logging AI product, ensuring high availability, performance, and reliability for millions of users.. Design, build, and refactor production-grade ML codebases. , applying advanced software engineering principles (e.g., modular design, clean architecture, testability, dependency management) to create robust and maintainable systems.. Deeply understand, implement, and improve LLM based AI products. , including fine-tuning embedding models for semantic search, advanced prompt engineering techniques, and efficient context management strategies.. Diagnose, debug, and resolve complex issues within ML pipelines. , including performance bottlenecks, data quality problems, and model accuracy.. Drive MLOps practices. for model deployment, versioning, monitoring, and A/B testing, ensuring seamless integration and continuous improvement in production.. Collaborate closely. with data scientists to transition models into production, with platform engineers on infrastructure and scalability challenges, and with product/design teams to translate user needs into technical solutions.. Stay at the forefront of ML research and technologies. , actively evaluating and integrating cutting-edge advancements (especially in LLMs, multimodal AI) into our product and engineering workflows.. Write clean, efficient, and well-documented code. across our microservices and data pipelines, contributing to a culture of engineering excellence.. Ship high-quality code to production frequently. , ideally on a daily basis.. 🧠 What You’ll Bring to the Table. 7+ years of professional experience in backend software engineering, with at least 5 years explicitly focused on the full lifecycle of deployed Machine Learning or AI products.. Proven expertise in designing, building, and extensively refactoring production-grade ML codebases, demonstrating strong command of software engineering best practices for complex, stateful systems.. Deep practical expertise working with productionised LLM based products. Experience with vector databases and similarity search.. Hands-on experience with embedding models and their fine-tuning for semantic search.. Prompt engineering.. Demonstrated ability to diagnose and troubleshoot complex issues. within ML pipelines, including performance, memory management, and data-related challenges.. Strong command of Pythonor Java. Extensive experience working on large-scale backend systems. , dealing with scaling challenges, high availability, and supporting a high volume of users in an ML context.. Hands-on experience with MLOps practices. , including model deployment, monitoring (e.g., drift, quality), versioning, and A/B testing ML systems in production.. Proficiency with cloud platforms. such as Google Cloud (preferred, including Vertex AI) or AWS (including SageMaker).. 🏆 Bonus Points - Not required, but WOW us!. Experience with multimodal AI, particularly in areas related to image/vision and text fusion.. Contributions to open-source ML projects, research papers, or conference presentations.. Experience with ML frameworks like TensorFlow, PyTorch, or scikit-learn.. Prior experience in data analysis or data science, providing a holistic understanding of the data lifecycle.. ✨ Our Hiring Journey. 👋 Stage 1: Talent Acquisition Screen | 40 mins. A friendly conversation with our Talent team to learn more about your background, motivations, and career goals. It’s also your chance to ask us anything about the role, team, or ZOE’s mission.. 🧠 Stage 2: Hiring Manager Screen | 30 mins. A deeper dive into your leadership and technical experience with the Hiring Manager. We’ll discuss how you approach building ML products and your initial views on ZOE’s domain.. 🎯 Stage 3: Remote Interview Loop. This final stage includes three focused interviews to assess your technical and leadership capabilities. These are typically spread over . three days. , but we’re flexible — we can combine them into one or two days depending on availability.. You’ll need to be successful in each interview to progress to the next. We’ll keep you informed with feedback and next steps after each session.. 📊 ML Engineering Coding Interview. | . 60 mins. Hands-on coding using a Retrieval-Augmented Generation (RAG) codebase. We’ll assess your ability to debug, analyze, and refactor. You’re welcome — and encouraged — to use AI assistants (like GitHub Copilot or ChatGPT), as that reflects how we work day to day.. 🛠️ System Design Interview. | . 60 mins. You'll design a scalable ML system from scratch. We’re looking to understand your architecture thinking, MLOps knowledge, and how you make and justify trade-offs.. 💬 Behavioural & Leadership Interview. | . 45 mins. A conversation to explore how you lead teams, navigate complexity, and align with ZOE’s values. We’ll discuss non-technical problem-solving, collaboration, and leadership principles.. 🎉 Offer Stage. If all goes well, we’ll move quickly to extend an offer and support you through the next exciting steps.. The experience, skills, and attributes listed above reflect what we believe will contribute to success in this role. If you're passionate about ZOE and the opportunity, but don't meet 100% of the criteria, we still encourage you to apply. We are committed to supporting growth and are happy to offer up-skilling opportunities where possible.. Remote Philosophy. ZOE is a remote-first company, meaning remote work isn’t just an option — it’s how we work best. We are intentional about building a distributed, high-performing team where collaboration, trust, and flexibility thrive.. We design our workflows around asynchronous communication and shared documentation to support autonomy, focus, and cross-timezone collaboration. While our teams work independently, connection and teamwork remain central to how we operate — through regular rituals, meaningful virtual interactions, and in-person gatherings every quarter. These include team offsites and a yearly company-wide retreat to build relationships, spark creativity, and have fun together.. Being remote-first also means we value outcomes over hours and trust our team members to manage their work in a way that suits their unique rhythm and responsibilities. This approach allows us to support a truly flexible work environment, while staying aligned with our mission and values.. At ZOE, working remotely doesn’t mean working alone — it means being empowered, supported, and connected, wherever you are.. Compensation Philosophy. We are committed to offering competitive and equitable compensation that reflects the value of each role and aligns with regional labor market standards. Our approach to compensation goes beyond just base salary — we offer a comprehensive package that includes base pay and stock options, ensuring that every team member is rewarded for their contributions to the company’s growth and success.. We believe that building a thriving team requires not only providing fair and competitive compensation but also fostering an environment where success is shared collectively. Our total compensation package is designed to support the well-being of our employees, recognise their individual contributions, and empower them to grow alongside ZOE.. Benefits & Perks. We understand the significant role our benefits play in motivating, inspiring and safeguarding our employees' well-being. Our benefits strategy is thoughtfully designed to echo our mission and values, recognising the diverse needs arising from different life stages of our ZOEntists.. Our approach to benefits takes an inclusive and flexible view of both personal and professional growth. From competitive health insurance and wellness packages to inclusive parental policies, building connection, and tailored professional development programs, we've got you covered.. At ZOE, we continue to build a benefits package that invests in our team members’ long-term personal and professional growth and wellbeing, adding to this list as it evolves.. Equal opportunities. We are committed to fostering a diverse and inclusive team where every individual can bring their authentic self to work. We believe that this is key to our success and are dedicated to positively impacting the tech industry. As part of our commitment to equal opportunities, we encourage candidates from underrepresented backgrounds to apply. We ensure a respectful and inclusive environment for all and do not discriminate on the basis of race, colour, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, marital status, disability, or age. If you require any accommodations during the interview process, please feel free to inform us, and we will make every effort to support your needs.