Lead ML Engineer / Scientist

Requirements:

• 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.

Nice to Haves:

• 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

What You'll Be Doing:

• Software engineering: e.g. testing + CI/CD, monitoring/alerting + disaster recovery
• MLOps: Terraform and AWS infra, ML governance for hundreds of models
• Data Engineering: distributed processing at terabyte scale
• Science: prove value of new methodologies / algorithms applied to cross-team domains, estimate and measure impact, mentor junior members in experiment design

Perks and Benefits:

• Unique opportunity to scale and advance the impact of Data Science at a leading company
• Direct impact on Wise's mission and millions of customers
• Ownership of the evolution of ML experimentation tooling and label quality
• Freedom to drive impactful proof-of-concepts of new methodologies and tooling