At a Glance
- Tasks: Drive AI innovation by building and optimising our ML/GenAI platforms.
- Company: Join Wise, a global fintech revolutionising money management.
- Benefits: Competitive salary, flexible work options, and a diverse, inclusive culture.
- Why this job: Shape the future of AI in finance and make a real impact.
- Qualifications: 6+ years as a Technical Product Manager with hands-on ML experience.
- Other info: Collaborative environment with opportunities for personal and professional growth.
The predicted salary is between 36000 - 60000 £ per year.
Overview
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. As part of our team, you will be helping us create an entirely new network for the world's money. For everyone, everywhere.
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.
- 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.
- 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:
The Wise Tech Stack, 2025 Edition Our Application Security Journey Platform Engineering KPIs Internal Platform as a Product at Wise Wise Engineering – https://medium.com/wise-engineering
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. Keep up to date with life at Wise by following us on LinkedIn and Instagram.
Senior/Principal Product Manager - Machine Learning and AI employer: hackajob
Contact Detail:
hackajob Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior/Principal Product Manager - Machine Learning and AI
✨Tip Number 1
Network like a pro! Reach out to current or former employees at Wise on LinkedIn. A friendly chat can give you insider info and maybe even a referral, which can really boost your chances.
✨Tip Number 2
Prepare for the interview by diving deep into Wise's products and their AI initiatives. Show us that you understand their mission and how your skills can help them achieve it. Tailor your examples to highlight relevant experience!
✨Tip Number 3
Don’t just talk about your past roles; demonstrate your hands-on experience. Bring along prototypes or projects you've worked on that relate to machine learning and AI. We love seeing what you can do!
✨Tip Number 4
Finally, apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you're genuinely interested in joining the Wise team. Let’s make it happen!
We think you need these skills to ace Senior/Principal Product Manager - Machine Learning and AI
Some tips for your application 🫡
Show Your Passion for AI: When you're writing your application, let your enthusiasm for AI and machine learning shine through. We want to see how excited you are about the potential of these technologies and how you envision contributing to our mission at Wise.
Be Specific About Your Experience: Don’t just list your past roles; dive into the details! Share specific projects where you’ve built data or ML products, and highlight any hands-on experience you have with tools like Sagemaker or MLflow. We love seeing concrete examples of your work!
Tailor Your Application: Make sure your application speaks directly to the role. Use the job description as a guide to align your skills and experiences with what we’re looking for. This shows us that you’ve done your homework and are genuinely interested in joining our team.
Keep It Clear and Concise: While we appreciate detail, clarity is key! Make your application easy to read by using clear language and structured formatting. We want to quickly understand your qualifications and how you can help us shape the future of AI at Wise.
How to prepare for a job interview at hackajob
✨Know Your Tech Stack
Familiarise yourself with the tools and technologies mentioned in the job description, like Sagemaker, MLflow, and Ray. Be ready to discuss how you've used similar tools in your past roles and how they can be applied to Wise's AI transformation.
✨Showcase Your Prototyping Skills
Prepare to share examples of prototypes or internal tools you've built. This role requires hands-on experience, so be ready to explain your thought process and the impact of your work on previous projects.
✨Communicate Complex Ideas Simply
Practice explaining technical concepts in a way that non-technical stakeholders can understand. This will demonstrate your ability to bridge the gap between data science and business needs, which is crucial for this position.
✨Embrace Ambiguity
Be prepared to discuss how you've navigated complex problem spaces in the past. Share specific examples where you structured ambiguous situations into clear, actionable outcomes, showcasing your problem-solving skills.