Wise
global technology company
LeadMLEngineer/Scientist
Neural analysis suggests this role is
optimal for mid candidates.
“Lead ML Engineer / Scientist at Wise. Skills: Machine Learning, Data Engineering, MLOps, Software Engineering, Data Science. Removing bottlenecks from Data Science workflows. Providing ML tooling for experiments”
What You'll Achieve.
Scale and advance the impact of Data Science in Servicing tribe; Direct impact on Wise’s mission and millions of customers; Own the evolution of ML experimentation tooling and label quality; Deliver services/tooling from proof-of-concept to MVP
Industry & Context.
Problem solving skills; Ability to help refine problem statements and propose solutions taking effort-impact-scalability tradeoff into account; Drive to solve problems for Data Scientists
What They're Looking For.
Must Have
Extensive experience with end-to-end distributed data systems, specially ML-centric, Previous experience as Data Scientist in large scale product team, Excellent Python and Software Engineering knowledge, Ability to work with Java if needed, Demonstrable experience collaborating with engineers on services, Drive to solve problems for Data Scientists, 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), Ability to engage and manage projects, Problem solving skills, Ability to help refine problem statements and propose solutions taking effort-impact-scalability tradeoff into account
Nice to Have
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 testing
What You'll Do.
Removing bottlenecks from Data Science workflows
Providing ML tooling for experiments
Developing Wise’s ML Label Platform
Driving high priority projects from proof-of-concept to MVP
Owning the evolution of ML experimentation tooling and label quality
Conducting presentations
Maintaining good documentation and progress updates for projects
Driving impactful proof-of-concepts of new methodologies and tooling
Software engineering (testing
MLOps (Terraform and AWS infra
ML governance for hundreds of models)
Data Engineering (distributed processing at terabyte scale)
Proving value of new methodologies / algorithms applied to cross-team domains
Estimating and measuring impact
Mentoring junior members in experiment design
How You'll Work.
Team & Collaboration
Collaborating with engineers on services; Working in a cross-functional and cross-team environment; Co-owning stakeholder management; Co-owning roadmap; Co-owning delivery; Co-owning onboarding
Communication Scope
Good communication skills; Ability to get the point across to non-technical individuals and back it up with data (and statistical analysis)
Process & Methodology
Engage and manage projects, Refine problem statements, Propose solutions, Consider effort-impact-scalability tradeoff
Full Job Description
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. More about [our mission](https://wise.jobs/our-mission) and [what we offer](https://wise.jobs/what-we-offer). 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 Servicing tribe – namely Fincrime, KYC and Customer Support squads. What you build will have a direct impact on [Wise’s mission](https://www.transferwise.jobs/what-we-do/) and millions of our customers. Our team is responsible for 1) removing bottlenecks from Data Science workflows, 2) providing ML tooling for experiments, 3) developing Wise’s ML Label Platform. Moreover, we are responsible for driving high priority projects from proof-of-concept to MVP, to service / tooling. We are looking for someone to own the evolution of ML experimentation tooling and label quality – at first for Fincrime teams, then for other squads in Servicing. You will co-own stakeholder management, roadmap, delivery and onboarding. You’re also expected to conduct presentations, demos and workshops, in addition to maintaining good documentation and progress updates for your projects. Additionally, you will have the freedom to drive impactful proof-of-concepts of new methodologies and tooling that bridge a gap for two or more teams in Servicing tribe. Here’s how you’ll be contributing: * Software engineering: e.g. testing + CI/CD, monitoring/alerting + disaster recovery * MLOps: Terraform and AWS infra, ML governance for
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