BNY★3.5 (5.5k)· London

Lead AI solution development on BNY’s ELIZA platform, working with LLMs/NLP, agentic systems, and retrieval architectures. You will set technical direction across pods, mentor juniors, and contribute to the AI Hub’s standards and reference architectures.

You will execute A/B tests, multivariate tests, and personalisation campaigns using platforms like Optimizely, VWO, and Adobe Target, working with analytics suites such as Google Analytics 4 and Adobe Analytics, plus CMS and CDP tools. The role drives daily execution of the Rapid Iteration & Optimisation framework, collaborating with Paid Media, CX, and Development teams to deliver performance-enhancing site updates.

Works with A/B testing tools (Optimizely, VWO, Adobe Target), analytics (GA4, Adobe Analytics) and CDPs (Segment, Tealium), plus basic HTML, CSS, JS. Executes daily high-velocity site optimisation and continuous improvement for global clients within WPP Enterprise Solutions, collaborating with Paid Media, CX, and Development teams.

The AA★3.1 (797)· London

You'll design enterprise AI solutions using Large Language Models, Retrieval Augmented Generation, AI agents, orchestration frameworks, and cloud-native architectures on Azure, AWS, or similar. Working with engineering, data, product, and security teams, you'll shape The AA's AI roadmap for its motoring products and services. No team size is stated.

You will work with Python, FastAPI/Flask, PostgreSQL, MySQL, BigQuery, GCP and/or AWS, and IAC/CI/CD tools to build production-grade data pipelines and MLOps infrastructure. You’ll join Ki’s commercial performance insights squad to upgrade algorithm decision data to a versioned event stream and support a Monte Carlo simulation engine for an algorithmic insurance carrier. The role is in an agile, cross-functional squad.

Synapri★0.0· London

You will use Python, SQL, PySpark, NLP, GenAI, and Azure with CI/CD to build end-to-end data science solutions. As part of a customer’s Journey Insights team, you will transform structured and unstructured customer interaction data into insights and production-ready models using machine learning, NLP, and generative AI.

IQVIA★3.7 (2.7k)· London

This Senior AI Platform Engineer role at IQVIA uses technologies like AWS, CUDA, PyTorch, Slurm, and Kubernetes. The position defines and delivers the infrastructure strategy for the company’s Large Language Model programmes, ensuring research is transformed into production-ready AI systems for healthcare.

UST★3.7 (1k)· London

You will design and build agent-based AI systems using Python, LangChain, LlamaIndex, and AWS, focusing on multi-agent orchestration, RAG pipelines, and LLM-powered application backends. At UST, a digital transformation solutions provider, you will deliver production-grade, agent-based AI solutions integrated into complex enterprise environments.

Capgemini★3.7 (11k)· London

Business Analysts work with SAP, Informatica, IBM, and Oracle to deliver enterprise data management, governance, compliance, and AI/ML solutions within Capgemini’s Insights and Data unit.

International SOS★3.4 (566)· London

Python, scikit-learn, TensorFlow, PyTorch, XGBoost, LangChain/LangGraph, RAG, AWS Bedrock/SageMaker, Azure/GCP, vector stores, SQL, Kubernetes, and Git. You will build production-grade generative and agentic AI solutions—RAG pipelines, multi-step agents, and predictive models—for the company’s product platform.

Zaizi★4.0 (5)· London

Quantize and deploy open-source SLMs (Gemma 3, Llama 3) and vision-language models using LiteRT/TFLite, ONNX Runtime, and ExecuTorch. Design knowledge graph pipelines and on-device graph databases in Python, Rust, or C++, and build MLOps pipelines for air-gapped environments. The team delivers deterministic, explainable, human-in-the-loop AI decision-support tools for UK Defence intelligence users.

You'll use Python and platforms like Braintrust, LangSmith, Arize, or Weights & Biases to build eval and observability pipelines for AI features, including scoring, hallucination detection, and CI/CD quality gates. You join the AI Engineering team at an AI consulting firm that builds digital products for clients like PayPal and adidas.

RBC★3.9 (5.5k)· London

You will drive the BI team's transition from Power BI to custom Databricks Apps, using React/Vue/Angular, REST, GraphQL, MCP, and DevOps tools (Git, CI/CD, GitHub Actions/Azure DevOps). You will build user-facing data visualisations and interactive analytics. You will mentor engineers and set technical standards.

RBC★3.9 (5.5k)· London

You will design, build, and maintain REST and GraphQL APIs and MCP servers using Python (FastAPI, Flask) serving ML models from Databricks for internal apps, CRM platforms, AI agents, and LLM applications. You will build middleware, prototype applications, and mentor junior colleagues in a team reporting to the Director, Data Science.

Capgemini★3.7 (11k)· London

Work with AWS, SageMaker, Docker, Kubernetes, ECS, Fargate, LLMs, vector databases, and multi-agent frameworks to build GenAI solutions. You will design agentic AI systems, integrate LLMs into business workflows, and implement LLMOps and observability for a global technology transformation company.

Lineten★2.6 (5)· London

Build cloud-native services using C#, .NET, Azure, and Microsoft Fabric with a Medallion architecture, while integrating AI/LLMs and automating infrastructure. You’ll own end-to-end development, data pipelines, and site reliability for a small startup team building internal and external data self-service solutions.

Arup★4.0 (352)· London

Python, Git/GitHub, pytest/unittest, CI/CD pipelines, AWS/GCP/Azure, Terraform/Docker, MATSim, Java, and PopulationSim. The Transport Modelling and City Modelling Lab teams build agent-based and activity-based models to solve urban transport challenges, using data and software engineering to plan future mobility systems.

You'll work with Python, PostgreSQL, MySQL, BigQuery, FastAPI, Flask, GCP/AWS, and CI/CD pipelines. You'll join the commercial performance insights squad to build data pipelines and event streams for monitoring algorithmic insurance underwriting, including Monte Carlo simulation.

Staff Machine Learning Engineer role at Sony Interactive Entertainment's Visual Computing Group, working with TensorFlow or PyTorch and Python for graphics and video processing. The team designs and deploys neural networks for game rendering and live streaming R&D. Requires 7+ years experience and publications at top-tier conferences.

Build production-grade generative and agentic AI using Python, scikit-learn, TensorFlow, PyTorch, XGBoost, LangChain/LangGraph, RAG, AWS Bedrock/SageMaker, Azure, GCP, vector stores, SQL, Kubernetes, and CI/CD for the company’s product platform.

You'll work with Python, Braintrust, LangSmith, Arize, Weights & Biases, and CI/CD. The AI Engineering team builds eval and observability pipelines for production AI features — designing scoring pipelines, monitoring quality signals, and wiring eval gates into promotion paths.

You will work with Java microservices, Spring Boot, Python, SQL, Snowflake, dbt, Airflow, LangChain, Sagemaker, and MLflow. The data science team builds ML solutions for risk-based decisioning, pricing, and operational automation in insurtech/fintech. This is a hands-on leadership role—you will lead and develop the team while setting technical standards.

You’ll build cloud-native apps with C#/.NET and Azure, design Microsoft Fabric and Medallion data pipelines, handle ETL/ELT, SRE, and integrate LLMs via OpenAI/Azure OpenAI. Based at startup Lineten Ltd., you’ll join a small team enabling internal and external data self-service analytics.

Deloitte★3.9 (14k)· London

You will work with Python, NumPy, Pandas, scikit-learn, LangChain, Hugging Face, LlamaIndex, Azure Machine Learning, Foundry, Git, and Agile practices. The team is Deloitte’s Tax Digital Innovation AI & Data Studio, which researches, builds, and delivers analytics and AI-driven solutions for tax and legal clients.

Work with Python, SQL, JavaScript/TypeScript, NumPy, Pandas/Polars, visualization libraries, and deep learning frameworks (PyTorch, JAX, or TensorFlow) to design and deploy full-stack data-driven applications and machine learning solutions. You will be embedded with Arsenal's Men’s First Team Analysis department, building tools that directly support coaching and analysis workflows.