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.

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.

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 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'll work with Python (FastAPI/Django), Svelte/TypeScript, and AWS to build features across a payments and discovery platform. Tab is a YC-backed travel fintech enabling 100,000+ global tourism businesses to accept payments in 100+ currencies.

Allianz★3.8 (3.4k)· London

You'll build production data/ML systems using Python, Docker, Kubernetes, Terraform, Azure, Azure DevOps or GitHub Actions, plus SQL, PySpark, dbt, and Microsoft Fabric. Joining a small agile team, you'll deliver real-time API endpoints serving 10M+ daily requests and evolve cloud infrastructure and

Build a high-performance LLM gateway in Go, working with Kubernetes, SQL databases, and distributed caching to route and secure AI traffic across 400+ providers. As a founding engineer at Requesty Ltd, you will design and scale this "Cloudflare for AI" infrastructure, currently processing 75B+ daily tokens for enterprises like Shopify and Pfizer.

Fine-tune and distill small language models (Llama, Mistral) using quantization (GGUF, AWQ), vLLM, TensorRT-LLM, FlashAttention, and frameworks like Apple MLX or llama.cpp. The founding engineer will own the model layer, shipping production AI for a pre-seed startup building privacy solutions for tier-1 banks.

You will build the AI platform for a London fintech that automates insurance claims, using LLMs, NLP, and ML for document ingestion, fraud detection, and coverage decisions. You will develop and deploy production-scale systems alongside founders and insurance domain experts.

You will build and optimize multi-agent AI systems using Python and LLM orchestration tools like Temporal or LangChain, plus observability and data pipelines. Tuza is a London fintech creating AI agents that automate manual banking workflows for partners like Worldpay and NatWest.

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.

Build UI components using Vue.js, React, or Angular, plus JavaScript, HTML/CSS, and Figma. You'll join TransPerfect TechOps, which develops workflow improvements, core services for the GlobalLink platform, and scalable client interfaces. Work within an Agile (SCRUM/Kanban) team.

NatWest Group★3.7 (1.2k)· London

Leading a team building cloud-hosted, event-driven microservices at NatWest Boxed, you will manage software and quality engineers across empowered squads while working with AWS, Google Cloud Platform, Java, Python, JavaScript, ReactJS, AngularJS, Kafka, Hadoop, PostgreSQL, Snowflake, and GitLab.

McKinsey & Company★4.2 (952)· London

You will work with deep learning, foundation models, Bayesian modelling, causal inference, LLMs, and computational chemistry/protein engineering. As part of McKinsey’s global scientific AI team, you help transform clients’ R&D in life sciences, chemicals, energy, and other scientific industries.

Imperial College London★4.2 (238)· London

You will use Python, PyTorch, NumPy, SciPy, Pandas, Anaconda, Jupyter and discrete-event simulation to develop performance, cost and reliability models for distributed Foundation Model inference across a Cloud-Edge-IoT computing continuum. The research, part of the f-inference project, focuses on KV-store caching policies, backpressure control, and stochastic multi-layer network models.