Senior/Principal Product Manager – Machine Learning and AI in London

Wise is a global technology company, building the best way to move and manage the world's money. Min fees. Max ease. Full speed. Whether people and businesses are sending money to another country, spending abroad, or making and receiving international payments, Wise is on a mission to make their lives easier and save them money.

Our Machine Learning and Generative AI Platform teams are at the forefront of Wise's AI transformation. We're building the foundations that enable our entire organisation to harness the power of AI safely and effectively. Our ML Platform provides cutting‐edge tools that turn data science ideas into production with minimal effort, while our GenAI Platform empowers all Wisers to leverage state‐of‐the‐art generative AI through seamless integration, robust governance, and best‐in‐class developer experience.

We're looking for a Technical Product Manager who can get their hands dirty. This isn’t a role where you’ll just write requirements – you’ll prototype solutions, analyse complex datasets, and work shoulder‐to‐shoulder with our engineering teams to shape the future of AI at Wise. You’ll navigate the rapidly evolving GenAI landscape while ensuring we move fast without compromising on security, privacy, or compliance. This is a unique opportunity to drive AI adoption across a global fintech, where your technical depth will be as valuable as your product sense.

How we work: We work differently and we’re proud of it. Our teams are empowered to solve the most urgent and relevant problems they see for our customers. We all share the responsibility of making Wise a success. We empower Wisers to make decisions and take ownership of how they work best. Teams and individuals have different needs — that’s why we have company‐wide principles, and then our teams set their own guidelines.

What will you be working on:

• Ship the AI platform that unlocks innovation: Drive adoption of our ML/GenAI infrastructure by identifying friction points through data analysis and shipping solutions that reduce time‐to‐production from weeks to days.
• Build and validate technical roadmaps using prototypes, SQL analytics, and hands‐on experimentation with our stack (Sžas, MLflow, Ray, Bedrock).
• Define success metrics and implement dashboards that track everything from model performance to business impact.
• Balance speed with safety: Design governance frameworks that enable rapid experimentation while ensuring compliance – automating risk assessments and privacy checks.
• Partner with security to implement model monitoring and access controls that protect customer data without blocking innovation.
• Create cost optimisation strategies backed by data, reducing ML infrastructure spend while scaling usage.
• Drive strategic technical decisions: Evaluate and select AI vendors through hands‐on technical assessment and ROI analysis.
• Work with engineering to define architecture that scales – from feature stores to multi‐cloud inference.
• Enable 10x more teams to use AI by building self‐service tools, clear documentation, and reusable shards.

Qualifications: What you need: We are fully aware that it is uncommon for a candidate to have all skills required and we fully support everyone in learning new skills with us. So if you have some of those listed below and you’re eager to learn more we do want to hear from you!

• You have 6 years of experience as a Technical Product Manager, with hands‐on experience building data or ML products.
• You can translate between the worlds of data science, engineering, compliance, and business stakeholders.
• You’ve built things yourself – whether it’s prototypes, internal tools, or production features.
• You’re an exceptional communicator who can explain complex technical concepts to non‐technical stakeholders.
• You thrive in ambiguity and can structure complex problem spaces into clear, measurable outcomes.
• You have hands‐on experience with data analysis tools (Python/pandas, Jupyter notebooks) and can independently analyse large datasets.
• You have experience shipping technical products that balance user needs with platform constraints.
• You understand ML workflows deeply – from data pipelines and feature engineering to model training and deployment.
• You can read and understand code well enough to debug issues, suggest improvements, and contribute to technical discussions.

Nice to have:

• Experience with modern ML stack (MLflow, Airflow, Sagemaker, Ray, Bedrock or similar).
• Hands‐on experience with LLMs – prompt engineering, fine‐tuning, or building RAG systems.
• Knowledge of streaming data systems (Kafka, Flink).
• Experience with Kubernetes, Docker, and cloud infrastructure.
• Previous experience building developer platforms or API products.

For everyone, everywhere. We’re people building money without borders — without judgement or prejudice, too. We believe teams are strongest when they are diverse, equitable and inclusive. We’re proud to have a truly international team, and we celebrate our differences.