You will work with Python, LLMs, agentic workflows, retrieval-augmented generation (RAG), and internal AI platforms. The Tactical AI Automations team deploys and supports AI tools across PIMCO's Portfolio Management and Analytics groups, including operational support for Lane Assist and POET (portfolio optimization tools).

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.

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.

You'll lead a 4–5 person team building machine learning systems using Python, TensorFlow, PyTorch, JAX, AWS, Docker, and Kubernetes for Super's Playstack platform, which powers sports betting and gaming experiences across Europe and Latin America. The role combines technical contribution, project management, and people leadership, focusing on predictive analytics, personalization, fraud detection, and real-time recommendations that enhance customer engagement in online gambling and sports betting.

Work with LLMs and vision models, fine-tuning, prompt engineering, and TypeScript. Develop and refine core models powering automated AML and KYC workflows for a YC S24-backed startup automating financial crime compliance.

Work with Python, NumPy, pandas, SQL, dbt, Snowflake/Databricks, and LLMs to build and deploy ML models and agentic systems (function calling, multi-agent orchestration) for Planday’s scheduling and workforce management platform. You’ll ship production features on a small, high-impact team.

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.

You'll develop Conveo's AI-powered consumer and B2B research platform using React, TypeScript, Node.js, PostgreSQL, and AWS/GCP infrastructure, with exposure to LLM APIs and prompt engineering. The role spans full-stack development—from API design to frontend implementation—plus direct customer interaction to translate research needs into technical solutions. You'll work autonomously on feature ownership within a small, high-performing engineering team at this Y Combinator-backed startup.

Work with Python, TypeScript, LLMs, RAG pipelines, agent architectures, MCP, eval frameworks, CI/CD, and cloud (AWS/GCP preferred). You will join a small pod to deliver end-to-end AI client engagements—building prototypes, MVPs, and integrating into enterprise environments.

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.

Circadia Health's ML Ops Engineer will work with Apache Airflow, AWS (Batch, EC2, S3, IAM, CloudWatch), MLflow, Docker, Python, Git, SQL, Snowflake, and edge devices. You own the ML infrastructure and pipelines for a clinical monitoring platform that identifies early signs of clinical deterioration using predictive models in cloud and edge environments.

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.

Design, implement, and deploy machine learning models; develop and optimize LLM solutions; work with Python, TensorFlow, PyTorch. This intern will program and fine-tune AI tools for the IT teams at Medpace, a full-service clinical CRO that provides Phase I-IV drug development services.

You will work with MongoDB, Postgres, Kinesis, Flink, Spark, ElasticSearch, Redis, Trino, Presto, Snowflake, Kubernetes, and public cloud. The Platform Engineering team designs and develops core data storage, streaming, caching, and indexing platforms that power Scale AI’s products for LLMs and generative models.

Accenture★3.9 (29k)· London

You will work with Python, LangChain, LangGraph, AutoGen, FastAPI, REST APIs, vector databases, Git, CI/CD, and cloud platforms (Azure, GCP, or AWS) to build, deploy, and iterate on machine learning and generative AI solutions for clients across industries.

You'll work with MCP, Python, TypeScript/Node, React, SQL, and UI protocols (A2UI, AG-UI, MCP-UI) to build agent loops, orchestration, and generative UI. The role owns AI capabilities end-to-end for commercetools' autonomous commerce platform, taking capabilities from prompt to production.

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.

You'll work with Python (FastAPI), Go, TypeScript, PostgreSQL, Redis, Pinecone/pgvector, AWS (ECS, Lambda, SQS), Docker, Kubernetes, Terraform, LangChain/LlamaIndex, vLLM, and Anthropic/OpenAI APIs. You'll build and optimize RAG pipelines, real-time inference APIs, and vector search infrastructure powering LLM features for 500k+ monthly active users.

WTW★3.6 (1.7k)· London

The Data Engineer will work with Microsoft Fabric, Azure Synapse, Azure Data Factory, PySpark, Python, Power Automate, and Copilot/AI tools to design, build, and optimize data pipelines. They will integrate AI/LLM models and Power Platform automation into data workflows, collaborating with data experts and business teams.

9fin★0.0· London

You'll work with Python, TypeScript, Docker, Kubernetes, AWS Bedrock, RAG, MCP, and observability tools like Arize Phoenix. The AI Engineering team builds the core platform for Generative AI, Agentic AI, and ML applications powering debt market products. You'll be one of a few senior engineers shaping the platform's architecture with the Engineering Lead.

Zoopla★3.9 (18)· London

Work with Python, scikit-learn, PyTorch, TensorFlow, AWS (SageMaker, ECS, Lambda, SQS, DynamoDB), and MLOps tooling to build end-to-end ML pipelines. You will design and deploy production ML models that bring intelligent automation and predictive capability to the UK property market, using Alto's large dataset of real housing transactions.

Ebury★3.3 (13)· London

You will work with React, TypeScript, Python, FastAPI, Strands Agents SDK, AWS Bedrock, RAG, Ragas, Langfuse, AWS/GCP, Terraform, and Docker. You will build Flow, an internal AI agent platform that orchestrates multi-step workflows across data warehouses and services to automate business operations. The role involves end-to-end ownership of agent workflows, reasoning UIs, and cross-system integrations.

Version 1★3.9 (39)· London

Work with Python, LLMs, RAG systems, fine-tuning, embeddings, orchestration frameworks, and AI coding agents to design, prototype, and scale enterprise-grade AI products. Lead applied research across LLMs, agentic systems, retrieval architectures, and applied ML for Version 1, a technology and transformation solutions provider.

Depop★4.4 (61)· London

PyTorch, large language models (LLMs), Transformers, Python, and MLOps tools. The role designs and builds scalable ML systems to detect fraud, abuse, and policy violations in user-generated content on a peer-to-peer circular fashion marketplace.