Wise★3.5 (42)· London

A Lead Data Scientist will work with Python, SQL, and machine learning models (classification, propensity, churn, next-best-action) using gradient boosting, neural networks, or linear models. They will design data pipelines and ML infrastructure for Wise’s Marketing CRM team, building recommendation systems to personalize customer communications. This individual-contributor role involves developing production models, running A/B tests, and influencing product strategy.

Faculty★0.0 (16)· London

Research Scientists execute technical research in AI safety, using Python with PyTorch to study and steer transformer-based LLMs via white-box and black-box interpretability techniques like mechanistic interpretability and steering vectors. They collaborate with senior scientists at Faculty, a company that builds and deploys human-centric AI for over 350 global clients.

Citi★3.9 (21k)· London

You will work with C++, C#, .NET, Java, Python, kdb, and SQL to develop analytics libraries and pricing models using Monte Carlo methods and PDE solvers. The role focuses on creating quantitative models for Citi’s cross-asset XVA and capital analytics, supporting trading business pricing and risk-management. You will collaborate with Traders, Structurers, and technology professionals.

You'll use Zapier, Make, n8n, Python or JavaScript, APIs, SQL, and webhooks. You'll own the automation layer for influencer marketing, building workflows for discovery, onboarding, contracts, content tracking, reporting, and payments.

Wise★3.5 (42)· London

The Data Engineering Manager will lead the Treasury Global Liquidity team, designing a real-time liquidity observability stack and building event-driven systems for automated investment, risk management, and machine learning-based cash forecasting. They will collaborate with product, data scientists, and finance stakeholders to deliver scalable solutions.

You'll work with Python, NumPy, SciPy, Pandas, PyTorch, JAX, and deep learning frameworks to build models using operator learning, geometric deep learning, or generative models. PhysicsX is building an AI-driven simulation software stack for multi-physics engineering and manufacturing across aerospace, energy, and other advanced industries.

Work with Java and/or Python to support the design, development, and maintenance of scalable applications. You will join the front-office engineering team of a fintech firm to help deliver high-impact, revenue-facing systems used by traders and product teams.

You will work with PHP, MySQL, HTML5, CSS, JavaScript, jQuery, React, Next.js, Laravel/Symfony, DevOps/CI/CD tools (Jenkins, Bamboo), Docker, and AWS. The team creates experiences through data and media management and data analytics engines, working on complex development for both industry-leading companies and startups.

Develop React applications using TypeScript and Node.js, running on Azure AKS with Azure PostgreSQL. Work with Terraform and Harness CI/CD pipelines, integrate RESTful APIs, and create end-to-end automation tests with tools like Selenium or Playwright.

You'll work with Python, SQL, Snowflake, and dbt to transform and model data, build data workflows, and automate processes. The role sits on the Python Infrastructure team at Lendable, a fintech company rebuilding consumer finance products like loans, credit cards, and car finance.

Wise★3.5 (42)· London

You will work with Java, Spring Boot, AWS, Apache Kafka, and potentially Trino. The Pricing Core team builds and maintains the main pricing platform that enables Wise to price its products, processing over 100 million requests daily across critical paths.

Work with Snowflake, dbt, Python, and SQL to transform and model data, build data workflows, and automate processes. You’ll join the Python Infrastructure team at Lendable, a fintech building credit and savings products.

DeepL★3.8 (4)· London

You’ll work with C#/.NET Core, Cassandra, gRPC, Kubernetes, and AI-assisted tools like Copilot and Claude. You’ll join the Identity and Access Management team, which owns DeepL’s full identity stack—organization, group, account, consent, session management, SSO federation, SCIM provisioning, and the OIDC provider.

JPMorgan★3.9 (20k)· London

Work with KDB, Q, AWS, and optionally Terraform, Kubernetes, Python, C, C++, or Java. Develop and maintain applications storing large Options data sets for real-time and historical access within JPMorgan’s Equities Trading Data & Analytics team, migrating to AWS and re-architecting systems.

You'll work with Python, SQL, Snowflake, and dbt to transform and model data, build data workflows, and automate processes. This role sits on the Python Infrastructure team at Lendable, a fintech building technology to help people get credit and save money.

You will work with PyTorch, TensorFlow, deep learning models, recommendation and retrieval systems, and MLOps practices on cloud infrastructure. Joining ASOS’s Outfits Discovery team, you will build and operate large-scale production ML systems that power personalised outfit recommendations and AI-driven fashion discovery for millions of customers.

You will use deep learning frameworks, distributed computing technologies, GPU-based training environments, and MLOps practices to build and deploy batch and real-time recommendation, ranking, and personalisation models. This role is within ASOS's Search & Recommendations team, which builds the machine learning systems that help millions of customers discover products daily.

Develop novel ML architectures including GNNs and foundation models using PyTorch or JAX. You will drive the core discovery engine of an autonomous laboratory, bridging simulation and real-world physical experiments for materials innovation.

Work with .NET, TypeScript, React, AWS, and CI/CD pipelines. Lead a small engineering team for a UK tech consultancy, owning technical delivery and architecture on client projects. Act as the technical face of projects from day one.

Work with Python, PostgreSQL, React/TypeScript, LLMs, prompt engineering and OpenAI evals to build production-ready algorithms and evaluation pipelines. As a founding AI engineer, you will develop proprietary AI for patent generation, delivering efficiency gains to 400+ global IP teams.

Develop novel machine-learning methods for molecular and protein discovery, using Python, PyTorch, graph neural networks, transformers, and diffusion models. Working at a life science technology company, the role involves research with engineering proximity, translating ideas into practical tools for scientific discovery. Preferred experience includes 3D and geometric deep learning, molecular generation, and protein modelling.

Work on high-dimensional statistical inference and theory, conducting complex simulation and real data analysis with advanced programming skills. The NeST project is a collaborative EPSRC Programme Grant on network stochastic processes and time series, led by a team of nine investigators across six UK universities.

You will work with Python, PyTorch or JAX, Docker, CI/CD, and cloud platforms to deploy ML models for protein design. The team builds scalable infrastructure for training, inference, and evaluation across molecular and protein datasets, taking research prototypes into production.

You will work with C#, Python, TypeScript, JavaScript, React Native, AWS or Azure, and various databases (relational, graph, document, key-value) plus SQL. The role supports critical projects aligned with Net Zero ambitions.

You will work with Java, Spring Boot, microservices, REST APIs, AWS, DevOps and CI/CD pipelines. You’ll lead client projects for a global technology consultancy, mainly in financial services, focusing on migrating legacy systems to AWS and introducing cloud deployments. As Principal Java Developer, you will lead projects, but team size isn’t specified.