Lead ML Engineer​/Scientist

Wise is a global technology company building the best way to move and manage the world’s money.

Min fees. Max ease. Full speed.

We’re looking for a Lead Machine Learning Engineer to join our growing Servicing Machine Learning and Data Engineering Team in London.

This role is a unique opportunity to scale and advance the impact of Data Science in the Servicing tribe – namely Fincrime, KYC and Customer Support squads. What you build will have a direct impact on Wise’s mission and millions of our customers.

• Own the evolution of ML experimentation tooling and label quality, starting with Fincrime teams and expanding to other squads in Servicing.
• Co‑own stakeholder management, roadmap, delivery and onboarding for these tooling initiatives.
• Conduct presentations, demos and workshops, and maintain good documentation and progress updates for your projects.
• Drive impactful proof‑of‑concepts of new methodologies and tooling that bridge gaps between two or more teams in the Servicing tribe.
• Software engineering: develop and maintain testing + CI/CD pipelines, monitoring/alerting and disaster recovery.
• MLOps: build and manage Terraform and AWS infrastructure, and establish ML governance for hundreds of models.
• Data Engineering: develop distributed processing solutions at terabyte scale.
• Data Science: prove the value of new methodologies/algorithms across cross‑team domains, estimate and measure impact, and mentor junior members in experiment design.

• Extensive experience with end‑to‑end distributed data systems, especially ML‑centric ones.
• Previous experience as a Data Scientist in a large‑scale product team or business.
• Excellent Python and software engineering knowledge; experience with Java is a plus.
• Strong drive to solve problems for Data Scientists, with the ability to work independently in a cross‑functional and cross‑team environment.
• Strong communication skills, able to explain concepts to non‑technical stakeholders and back them up with data and statistical analysis.
• Ability to refine problem statements and propose solutions, balancing effort, impact, and scalability.
• Experience collaborating with engineers on services.

• Apache Spark, Iceberg, Kafka, dbt
• Scikit‑Learn, XGBoost, PyTorch, MLflow, Graph Frames, Ray
• AWS (S3, EMR, Sage Maker, Lake Formation), Terraform, Docker, Git Hub CI/CD
• Knowledge graphs (RAG), graph ML, probabilistic programming, A/B testing

We believe teams are strongest when they are diverse, equitable and inclusive. We celebrate our differences and strive to create an environment where every employee feels respected and empowered to contribute towards our mission and progress in their careers.