Google★4.3 (6.2k)· London

Manage engineers building Google’s Learning Platforms within the Global Business Organization, which powers Google’s ecosystem of products and services for customers and partners. Work with back-end languages (Java, Python, Golang, C++) and front-end (JavaScript, TypeScript, HTML, CSS), plus ML model fine-tuning and evaluation.

Work with Python, PyTorch (or JAX/TensorFlow), RL fine-tuning frameworks like TRL or verl, and distributed multi-GPU training. The Reinforcement Learning Team advances RL, Bayesian optimisation, AI agents, LLMs, and vision-language models, applying them to AI for science, chemistry, physics, and robotics while publishing at top venues.

This role develops generative AI applications using Java, Python, React or Angular, LangChain, LlamaIndex, Hugging Face, Docker, Kubernetes, and AWS, with tools like GitHub Copilot. You will build scalable, AI-powered solutions for Citi’s global finance operations.

Work with Nvidia GB200 72NVL CX8 and AMD MIxxx architectures, coding in C, C++, C#, Java, JavaScript, or Python to benchmark, profile, and debug GPU clusters. You will help build foundational models powering Microsoft’s personalized AI assistant, Copilot, spanning training and inference infrastructure, model architecture, and data curation.

White & Case★4.0 (120)· London

Works with Python, JavaScript, MCP, agentic AI frameworks, LLMs, and cloud platforms (Azure, AWS) to architect and deploy AI tools. As technical lead of the Applied AI Lab, the role oversees design, development, testing, and deployment of AI solutions to support legal practice and firm-wide innovation. Manages and develops a multidisciplinary team of legal engineers.

You will work with Python, JavaScript, Model Context Protocol (MCP), agentic AI frameworks, LLMs, and cloud platforms (Azure, AWS). As technical

Citi★3.9 (21k)· London

Build and scale AI-powered financial systems using Java, Spring, React/Angular, Python, FastAPI, Docker, and GitHub Copilot within Citi’s global tech environment. You will design generative AI agents, LLM workflows, and RAG pipelines while working on enterprise microservices, mobile, or front-end development. This role is for an individual contributor on an agile team.

Fitch Ratings★3.8 (136)· London

You'll build ML/AI solutions using Python, FastAPI, PyTorch/TensorFlow, LangChain, LangGraph, and React/TypeScript within cloud-based microservices architectures. The agile team delivers software products for Fitch's BMI business, which provides data-driven market insights and risk analysis to customers globally. You'll design full-stack enterprise applications, implement GenAI features with LLM integration, and establish development best practices across the product suite.

Deloitte★3.9 (14k)· London

You will work with Python, JavaScript, Kafka, Azure, Kubernetes, Terraform, Helm, LangChain, PySpark, Databricks, and ADLS. You will design, develop, and deploy production-grade GenAI and machine learning systems for the GenAI team within Deloitte’s Data & AI organisation.

Staff AI Engineer will use Python, Azure, LangChain, Semantic Kernel, LLMs, and RAG to build production-ready patterns for agentic AI, prompt engineering, and responsible AI. This cross-cutting role connects AI ambition to delivery across all Tech domains at Sainsbury's, creating reusable accelerators and standardising AI engineering division-wide.

Work with PyTorch or TensorFlow, Python, Docker, Kubernetes, GCP, and MLOps tools (CI/CD, feature stores, model serving) on the ML Recommendations team. You will own problems end-to-end—from data exploration to production deployment—building personalized recommendation and ranking systems for Bumble’s dating and friendship platform.

You will work with LLMs, generative AI, Python, JavaScript, React, HTML, CSS, Microsoft Azure, and DevOps tools (CI/CD, Git). You will design, build, and deploy AI applications that enhance productivity, automate workflows, and support business decision-making across a growing technology function.

Checkout.com★3.8 (15)· London

You will work with LLMs (GPT, BERT, Llama, Gemini), Python/JavaScript, AI frameworks (LangChain, PydanticAI), cloud platforms (AWS/GCP/Azure), Docker, Kubernetes, and Terraform. As part of Checkout.com’s AI Centre of Excellence, you will design, build, and deploy Generative AI solutions (chatbots, assistants, knowledge extraction tools) to enhance products and streamline business processes.

Flo Health★4.8 (26)· London

Lead a team building shared AI infrastructure powering Flo’s chatbot, cycle predictions, and health insights. Work with Databricks, OpenAI, Anthropic, and AWS, managing MLOps, model serving, and LLM stacks in production.

Trainline★3.9 (17)· London

You'll work with Python, Pandas, NumPy, Scikit-learn, Spark, Docker, Terraform, MLflow, CI/CD, and LLMs (fine-tuning, RAG, agents). The team builds production ML and AI solutions powering Trainline's search, recommendations, pricing, routing, personalization, digital marketing, and customer support across rail travel.

Works with Azure cloud, LLMs, vector search, MLOps, CI/CD, data pipelines, and machine learning techniques like NLP. Leads design and delivery of AI/ML solutions across multiple squads to support the bank’s AI strategy.

You will work with Python, TypeScript/JavaScript, Java, or C++ and cloud platforms (AWS, GCP, Azure) to build and deploy end-to-end generative and agentic AI applications, create training datasets, and design evaluation pipelines for LLMs. The Global Public Sector team builds custom AI applications for government clients, impacting millions of citizens.

Build and maintain scalable backend data services using Python, FastAPI, SQL, Docker, Kubernetes, and CI/CD pipelines. You’ll work on the Signal Ocean platform—an AI-driven intelligence system for shipping and commodities—within the Modelling & Data Services team, collaborating with data science and product.

You'll architect and deploy AI systems generating ad creatives using LLMs, vision and diffusion models, code generation, and multimodal asset generation, working with Python, JavaScript/TypeScript, and HTML. The Creative GenAI team at Liftoff—an AI-powered performance marketing platform serving 6,600+ mobile businesses—tackles end-to-end creative production including interactive playables, from prototyping through production pipelines. You'll report to the Senior Director of Creative GenAI, mentor engineers, and drive innovation in generative AI for ad tech.

Thomson Reuters★3.9 (4.3k)· London

You'll work with PyTorch, JAX, HuggingFace Transformers, vLLM, LLM APIs, Ray, Spark, and experiment tracking tools like Weights & Biases and MLflow on Thomson Reuters' Foundational Research division, which develops advanced algorithms and training techniques for Large Language Models including LLM training, post-training techniques for reasoning and workflows, data-centric ML, and evaluation. You'll design and implement scalable systems for training, fine-tuning, and evaluating LLMs while translating cutting-edge research into production implementations.

LSEG★3.7 (402)· London

You'll lead a team of quantitative analytics and AI engineers building LLM-powered analytics solutions using Python, cloud platforms (Azure preferred), Databricks, Snowflake, and orchestration frameworks like LangChain and AutoGen. The role focuses on developing next-generation AI-driven analytics and agent-based systems for LSEG's financial markets clients through its Microsoft partnership, with responsibilities spanning LLM engineering, cloud-native architecture, MLOps, and team leadership. You'll manage engineers while architecting scalable data pipelines, RAG systems, and API-first SaaS/PaaS products for risk modeling and intelligent reporting.

JPMorgan★3.9 (20k)· London

You'll work with Java, low-latency real-time systems, high-throughput messaging APIs, and middleware to design and develop equities algorithmic trading strategies and execution platforms. You'll collaborate with quants, traders, and technologists globally at JPMorgan's Electronic Client Services desk—a market-leading agency flow execution provider—developing simulation environments, enhancing strategies, and maintaining the trading engine across multiple technical areas.

JPMorgan★3.9 (20k)· London

You'll develop and maintain a market-leading equities algo execution platform using Java, focusing on low-latency real-time trading systems, high-throughput messaging APIs, and simulation environments. Working across JPMorgan's Electronic Client Services desk—the top EMEA agency flow provider—you'll collaborate globally with quants, traders, and technologists on trading engine infrastructure, quantitative models, and strategy optimization. This VP-level leadership role involves designing algo strategies, enhancing performance through analytics, and driving operational stability across the global platform.

This Senior CX Software Engineer role involves designing and delivering distributed systems using functional programming languages like Scala, Haskell, or F#, with expertise in CQRS, event sourcing, and cloud deployment. You'll work with Digital Asset's CX team to help enterprise financial clients implement Daml-based solutions for multi-party workflows, from requirements and solution design through production deployment, requiring 5+ years of software engineering experience and ability to advise senior-level clients on complex distributed computing challenges.

Flow Traders, a proprietary trading firm, seeks a Senior Research Engineer to lead development of their trading model research framework using Python, PyTorch, Polars, Pandas, Ray, AWS/Azure/GCP, Docker, and Kubernetes. You'll design end-to-end ML pipelines for training and deploying trading models in production, then partner with Quantitative Researchers to develop data-driven systematic trading strategies and alpha signals.