Lead ML Engineer / Scientist
Summary
the pitchJoin Wise, a global technology company on a mission to make money management easier and more affordable for everyone. As a Senior Machine Learning Engineer, you will play a crucial role in advancing the impact of Data Science within the Servicing tribe, focusing on Fincrime, KYC, and Customer Support. You will own the evolution of ML experimentation tooling and label quality, drive high-priority projects, and have the freedom to explore new methodologies and tooling.
Role
posted by companyA bit about you:
Extensive experience with end-to-end distributed data systems, specially ML-centric ones;
Previous experience as Data Scientist in large scale product team / business;
Excellent Python and Software Engineering knowledge. Ability to work with Java if needed. Demonstrable experience collaborating with engineers on services.;
Strong drive to solve problems for Data Scientists, with the ability to work independently in a cross-functional and cross-team environment;
Good communication skills, ability to get the point across to non-technical individuals and back it up with data (and statistical analysis), to engage and manage project stakeholders;
Strong problem solving skills with the ability to help refine problem statements and propose solutions taking effort-impact-scalability tradeoff into account.
Some skills that will make you stand out:
Apache Spark, Iceberg, Kafka, dbt
Scikit-Learn, XGBoost, PyTorch, MLFlow,, GraphFrames, Ray
AWS (S3, EMR, SageMaker, Lakeformation), Terraform, Docker, GitHub CI/CD
Knowledge Graphs (+ RAG), graph ML, probabilistic programming, A/B testing
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.
Key responsibilities
- Lead the evolution of machine learning experimentation tooling and label quality, initially for Fincrime teams and then for other squads in Servicing.
- Co-own stakeholder management, roadmap, delivery, and onboarding for machine learning projects, and conduct presentations, demos, and workshops.
- Drive impactful proof-of-concepts of new methodologies and tooling that bridge gaps for two or more teams in the Servicing tribe.