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Wise

Low-cost international money transfers with API

Lead Data Scientist - Agentic AI, AML

AI Application EngineeringConfirmed live in the last 24 hours
Full-timeLondon, UK

About the Job

Requirements

  • Experience implementing, training, testing, and evaluating the performance of machine learning systems.
  • Strong knowledge of Python; familiarity with object-oriented programming principles is an advantage.
  • Professional exposure to generative AI or large language model solutions, such as prompt engineering, evaluation, language-model-powered workflows, or agentic AI.
  • Knowledge and experience developing and evaluating generative AI and large language model solutions, including automated evaluation harnesses and prompt engineering.
  • Experience with statistical analysis, experiment design, and failure-mode analysis in machine learning or large language model systems.
  • Ability to work independently across functions and teams with a product mindset.
  • Ability to communicate technical information to non-technical individuals and subject-matter experts.
  • Strong problem-solving ability, including refining problem statements and determining solutions.

Responsibilities

  • Lead the development and deployment of AI models that augment operational workflows, including Business and Consumer enhanced due diligence language models for case summaries, red-flag generation, risk classifications, document requests, and agentic workflows.
  • Establish labeling taxonomies and guidelines with enhanced due diligence subject-matter experts, construct evaluation datasets, and implement automated evaluation harnesses to measure accuracy, precision, recall, and failure modes.
  • Audit existing prompts and run structured experiments, including few-shot prompting, chain-of-thought, and context ordering, within a hypothesis-driven testing framework to reduce hallucinations, formatting errors, and prompt drift.
  • Help design and develop AI workflows that reason across multiple steps, use tools and contextual information, and safely and reliably support complex operational processes.
  • Design shadow-mode deployments and parallel execution testing to evaluate prompts and AI workflows at scale, and implement post-deployment monitoring for data and output drift.
  • Own the production pipeline by writing and deploying production-ready Python services, bypassing engineering bottlenecks where necessary while maintaining code quality.
  • Design human-in-the-loop systems in which AI provides recommendations and drafts while human operators retain final decision-making authority for critical financial crime mitigation assessments.
  • Analyze upstream data and create strategies to deflect financial crime attempts before they reach operations, reducing manual workload.
  • Set technical direction, mentor Senior and Junior Data Scientists, foster a product-focused mindset, and guide complex technical implementations, architectural decisions, and AI governance standards.

Desired Qualifications

  • Familiarity with automating operational processes through technical solutions such as large language models, AI agents, or multi-step AI workflows.
  • Experience implementing fine-tuning, reinforcement learning alignment, and evaluation techniques within a large language model training pipeline.
  • Familiarity with agentic frameworks such as LangGraph or similar.
  • Experience designing tool-using agents, orchestration workflows, or human-in-the-loop AI systems.
  • Willingness to review many historical operational cases.
  • Working knowledge of Java.

About the Company

Wise

Low-cost international money transfers with API

Wise enables international money transfers with lower fees by using a peer-to-peer model to match transfers across borders. It offers a multi-currency account for holding and managing money in different currencies and provides an API for businesses to integrate Wise transfers into their platforms. Unlike traditional banks that charge higher fees and poor exchange rates, Wise uses transparent, small-per-transaction fees and real-time exchange rates to reduce costs. Its approach differentiates it from competitors by emphasizing simplicity, cost transparency, and a broad API for business integration. The goal is to make cross-border payments cheaper, faster, and more transparent for individuals and businesses around the world.

Company size
10,001+
Company stage
IPO
Headquarters
London, United Kingdom
Founded
2011

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