Machine Learning Engineer

ML Engineer (Biometrics) - FinTech Hybrid working – three days per week in the London office. Highly competitive renumeration depending on experience and meaningful equity in the business! Permanent - Central London Own the algorithm behind a technology that is changing how people pay and access venues. The Role A fast-growing FinTech company is looking for its first dedicated Palm ML Engineer to take ownership of the machine learning technology at the heart of its platform. The business is building palm-biometric payment and access infrastructure that allows people to pay, enter venues and interact with services using nothing but their palm. The technology is already live across hospitality and fitness venues in the UK and Ireland. The company was founded by a team with backgrounds in high-growth fintech and is operating at the intersection of AI, biometrics, payments and hardware. With a small, highly technical team, this is an opportunity to have genuine ownership over a core piece of technology rather than owning a small part of a large ML pipeline. The Palm ML Engineer will own both the matching algorithm and the data that trains it. At this stage of the company's development, those two areas are intrinsically linked, and the successful candidate will have end-to-end responsibility for understanding, improving and deploying the system. Key areas of ownership will include:

• Matching Algorithm
• Evaluation & Performance
• Template & Capture Quality
• Data Pipeline
• Real-World Enrolment
• How They Work The organisation is AI-native and expects engineers to use AI tools as part of their everyday workflow, including Claude and other leading AI development tools. The expectation is that AI will significantly increase what one engineer can produce. However, the successful candidate will need to bring the judgement required to determine whether an evaluation is sound, whether a model is genuinely improving and whether a solution is appropriate for production. The Ideal Candidate The organization is not necessarily looking for someone with previous biometrics experience. The ideal candidate will have:
• 2–6 years of applied machine learning experience, including ownership of at least one model that has been deployed into production.
• Experience with metric learning, embeddings, verification or retrieval.
• Experience working with significant class imbalance where false positives have meaningful real-world consequences.
• A strong quantitative foundation, ideally with a STEM undergraduate degree and a Master's degree or equivalent depth in machine learning, statistics or mathematics.
• Strong Python skills and experience with PyTorch or an equivalent ML framework.
• Experience owning data pipelines and ML systems end to end.
• A willingness to work beyond the notebook and engage directly with real-world data collection and capture challenges.
• Strong analytical and problem-solving skills, with the ability to assess model performance objectively. What the Role Offers
• The opportunity to become the first dedicated ML engineer working on the company's core biometric algorithm.
• Genuine ownership of the algorithm, data, evaluation framework and definition of what "good" looks like.
• The opportunity to work across machine learning, biometrics, payments, hardware and real-world deployment.
• Meaningful equity in an early-stage business following two successful financing rounds.
• Competitive base salary plus equity, with transparency around compensation from the out
• The opportunity to work closely with a small, highly technical founding team and have a direct influence on the direction of the technology.