Job Description
About the role
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, analyze 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 (Sagemaker, 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 optimization 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 components
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 are 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 analyze large datasets
You have a track record of 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
Interested? Find out more:
Additional Information
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.
Inclusive teams help us live our values and make sure every Wiser feels respected, empowered to contribute towards our mission and able to progress in their careers.
If you want to find out more about what it's like to work at Wise visit Wise.Jobs.
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