Checkout.com★3.8 (15)· London

Senior Engineering Manager leading the Disputes team, which builds tools, services, and machine learning models to help merchants manage and win chargeback disputes at scale. The team owns a full stack centered on .NET / C#, React and TypeScript front ends, Python-based ML, and event-driven microservice architectures.

FDJ UNITED★4.0 (96)· London

You'll lead a DataOps/MLOps team building an ML platform and data operations capability for FDJ United's Sportsbook, working with AWS, Terraform/CloudFormation, Spark, Kafka, and CI/CD pipelines for end-to-end ML lifecycle management. The role involves establishing best practices, monitoring, and governance while collaborating with Data Engineering, ML Engineering, Quants, and Data Science teams to personalize customer experiences and manage risk.

Lead 6-7 engineers on core ML infrastructure for a systematic quant fund: distributed model training, LLM hosting/fine-tuning, and scalable deployment. Use Python with working knowledge of C++/Java. Own technical direction for real-world, high-stakes systems.

Manage the SAIL platform built with AWS, Kubernetes, Python, and infrastructure-as-code tools, enabling clients to control and leverage data through ML solutions embedded into business processes. Lead and mentor a squad of 4-6 engineers.

AXA★3.9 (2.9k)· London

Design and implement secure architectures for enterprise security and AI/ML initiatives across AXA, using Docker, Kubernetes, cloud security, API security, micro-services, MLOps/MLSecOps platforms, threat modeling, and SSDLC. Defines technical security standards and reference architectures aligning with frameworks like NIST AI RMF and ISO/IEC 42001. Reports to the Chief Security Officer.

Deloitte★3.9 (14k)· London

Lead client engagements designing and implementing advanced analytics and AI-driven Revenue Growth Management solutions, using Visualfabriq for TPO/TPM. You will advise consumer/healthcare clients on AI, machine learning, and predictive analytics to enhance commercial strategy. This role leads matrix project teams including offshore/nearshore resources.

This is a partnerships and business-development role, not a hands-on engineering position. You will work directly with founders, ML researchers, and scientists to create a global data-acquisition strategy for the company’s AI biology models. You will identify, negotiate, and secure complex data partnerships with health systems, biobanks, academic groups, and pharmaceutical companies.

Intercom★3.5 (4)· London

You will lead product engineering teams building Fin’s Customer Agent, a single AI agent that works across support

Engineering Managers at Ki lead teams working with Java, Python, JavaScript, Node.js, Spring Boot, Flask, Kotlin, GCP, and CI/CD tooling. Ki is the biggest global algorithmic insurance carrier, using machine learning and LLMs on its broker platform to digitise Lloyd's of London underwriting. The role collaborates with the CTO on technical strategy for the architecture, tech stack and infrastructure.

This senior director will shape marketing data strategy, working with first-party data, machine learning, marketing technology, AI, and analytics platforms. They join the Data & Analytics organisation at Forbes Advisor to build products and intelligence that power marketing and revenue growth. They will lead strategic initiatives across marketing measurement, customer intelligence, and data products, acting as a key technical counterpart to the VP of Data Strategy.

You will work with Java, Python, JavaScript, Node.js, Spring Boot, Flask, Kotlin, GCP, CI/CD, DevOps, GitOps, and Jira on microservice-based architectures. Ki is an algorithmic insurance carrier using machine learning and large language models to deliver broker quotes in seconds, and you will lead engineering for its core broker platform enabling underwriting at scale.

Lead a multidisciplinary engineering team building Meshh's cloud analytics platform, working with AWS, IoT sensors, CI/CD, infrastructure as code, and DevOps practices. The team delivers spatial analytics from wireless sensor data using AI and machine learning to produce actionable visitor insights for global customers.

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.

You will work with Gen AI, Cloud/Back-End/TypeScript, and Product Systems on Physical AI applications that bridge software and hardware. You lead and mentor an agile team of 5, integrating work across these three verticals.

Deloitte★3.9 (14k)· London

Work with SQL, Python, R, and cloud technologies to design end-to-end AI and data solution architectures for clients, developing strategic roadmaps and proof of concepts. Collaborate with on-shore and off-shore development teams in an Agile environment.

Deloitte★3.9 (14k)· London

Works with cloud platforms AWS, Azure, GCP, Databricks, Snowflake and GenAI. Leads complex AI and data transformations for clients within the Strategy, Governance and Architecture team, designing architectures for data sourcing, APIs, machine learning and data monetisation. The Senior Manager guides multidisciplinary delivery teams and mentors junior colleagues.

This role uses React, React Native, Node.js, DevOps and CI/CD. You will lead multiple cross-functional Agile teams delivering customer-facing web and mobile platforms and enterprise-scale digital products.

You’ll build scalable Python backend services and high‑quality frontends with Next.js, working across sensor ingestion, clinical knowledge graphs, and protocol engines. Healf Zone combines customers’ bloods, wearables, tests, and lifestyle data into personalised, ongoing wellbeing guidance. As founding engineer, you set the architecture, lead multiple pods (intelligence engine, diagnostics, companion app), and hire the team.

You'll build and lead a team of 10+ engineers developing a compiler stack for Fractile's novel AI accelerator hardware, using technologies like MLIR or TVM to enable industry-leading LLM inference performance. The company is designing a full-stack AI accelerator from the ground up; the compiler team works closely with hardware, driver, runtime, and ML engineers across the stack.

DeepL★3.8 (4)· London

You will manage a distributed engineering team owning payment gateway integrations, fraud/bot protection systems, and the self-serve checkout and conversion pipeline. The team works with AWS, Docker, Kubernetes, gRPC, REST, and both relational and NoSQL databases to drive user activation and monetisation while preventing abuse.

Lead a hands-on engineering team building a greenfield Agentic AI Platform for banking workflows using Python, Java/Spring Boot, and Go, with LLM/agentic frameworks (Google ADK, LangChain), GCP, Vertex AI, Elastic, Pinecone, Databricks, Kafka, Kubernetes, and Terraform. You will drive architecture, code, and mentor a new team of software and ML engineers.

Citi★3.9 (21k)· London

Lead architecture and hands-on development of a greenfield Agentic AI Platform on GCP using Vertex AI, ADK, LangChain, multi-agent architectures, and RAG with Python, Java/Spring Boot, and Kubernetes. The platform empowers Citi’s corporate and investment bankers with autonomous agents to streamline workflows and deepen client relationships.

Manages cloud (GCP), container (Kubernetes/Docker), Zero Trust, and IAM security using AI and automation. Leads engineering for Isomorphic Labs' digital biology platform applying frontier AI to drug discovery and novel therapeutics. Builds and scales a security engineering team, reporting to the CISO.

Accenture★3.9 (29k)· London

Design, build, and operationalize AI/ML solutions using Python, TensorFlow, PyTorch, Deep Learning, Generative AI, LLMs, and MLOps/LLMOps pipelines. The role delivers production-ready outcomes for enterprise clients across the full solution lifecycle, from assessing data to deploying scalable systems on cloud, HPC, and edge devices.

Data Scientists will use Python, SQL, Dune, and agentic frameworks to build production-ready analytical and agentic solutions on Cognite Data Fusion. This role leads and develops the Data Science community across Europe, ensuring delivery excellence for industrial customers.