Monzo★3.5 (108)· London

You will work with LLMs, autonomous agents, RAG, sequence-based architectures, Python, SQL, and Go, developing and deploying machine learning models in production. You’ll lead the design of a human-in-the-loop system that predicts, identifies, and routes customer problems to scale support for Monzo’s banking products across multiple geographies.

You will work with Python, AI coding agents (e.g., Claude Code, Codex), and potentially AWS, Kubernetes, and Temporal. Unitary builds Virtual Agents — AI-powered software workers that automate complex workflows end-to-end in customer tools, focusing on commercial insurance, marketplaces, and primary healthcare.

You will use TensorFlow or PyTorch, Python, and CV/graphics libraries, plus 3D engines like Unreal or Unity, to develop generative models for graphics and video. As part of the Visual Computing Group, you'll design neural networks and ML for PlayStation's game rendering and live

Native Kotlin and Jetpack Compose development on a consumer-facing Android app for in-store grocery trips, running on a known device inside live stores. Integrates on-device edge AI (ML Kit, TensorFlow Lite) and uses AI coding tools like Cursor or Claude Code. Reports to the Head of Android.

Use deep learning frameworks, distributed computing, GPU-based training, and MLOps to build and deploy batch and real-time ML models. The Search & Recommendations team develops personalised recommendations, product ranking, and AI styling experiences for ASOS's online fashion platform, helping customers discover products.

You'll work with PyTorch, TensorFlow, XGBoost, GPUs, CI/CD and containerisation on the Search & Recommendations team, building production-grade ML systems for personalised recommendations, product ranking and AI-driven styling at ASOS, covering the full lifecycle from experimentation to deployment.

Senior Machine Learning Engineer at ASOS, building production ML systems for personalized outfit recommendations and style discovery. You'll work with deep learning frameworks like PyTorch/TensorFlow, distributed GPU infrastructure, and MLOps practices including CI/CD, containerization, and observability. Collaborate with ML Scientists on batch and real-time models serving millions of customers.

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.

Wipro★3.8 (17k)· London

You will work with GenAI, LLMs, RAG, agentic frameworks, cloud platforms, DevOps, MLOps, and data governance. As an AI Strategic Advisor, you will define enterprise AI strategy, lead integration of generative and agentic AI, and architect full lifecycle AI initiatives for a global technology consulting firm.

Machine learning engineers at this tech-centric prop trading firm will work with Python tools and libraries, plus ML frameworks like JAX or TensorFlow, building training and inference infrastructure. The role focuses on enhancing research workflows and designing APIs for the growing ML team, applying techniques such as neural networks, random forests, and ensemble methods.

Use Python, PyTorch, TensorFlow, scikit-learn, LLMs, NLP, and SQL to build and deploy ML models for trade surveillance. You'll enhance analytics that detect market manipulation by analyzing trader behavior and order execution. Collaborate

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.

Data Idols★0.0· London

You will use Python, machine learning, recommender systems, LLMs, Generative AI, conversational

You will work with Python, PyTorch, TensorFlow, and causal inference tools (DoWhy, EconML, CausalML) to build production AI pipelines, APIs, and microservices. You will design and deploy behavioural, sequential, and causal AI models into Digital Twins, agentic decision engines, and intelligent automation. No team size is specified.

HSBC★4.0 (16k)· London

Work with Python, Docker, Kubernetes, Flask/FastAPI, PyTorch/TensorFlow, SQL Server/Postgres, and CI/CD pipelines to build and deploy production-grade ML and GenAI services. You will join the Growth AI programme within HSBC’s Corporate & Institutional Banking Data & Analytics, developing AI applications to identify business opportunities and mitigate client attrition.

Manage a team of test and DevOps engineers building CI/CD, Yocto-based embedded Linux, test automation, and cloud infrastructure (Python, C/C++, AWS/GCP/Azure) for non-invasive neuromonitoring medical devices.

You'll build scalable data infrastructure for AI applications using Python, SQL, Spark, dbt, LangChain, and cloud platforms (AWS, Azure, GCP), working with data pipelines, embeddings, vector search, and LLMOps tools like Terraform and LangSmith. QuantumBlack, McKinsey's AI division, develops next-generation AI systems and enterprise solutions for clients across industries. You'll collaborate with Data Scientists and ML Engineers in cross-functional Agile teams based in London, supporting the firm's AI adoption and complex problem-solving at scale.

You will work with Python, PyTorch, JAX, and TensorFlow to develop optimisation, control, and machine learning methods including reinforcement learning and physics-informed ML. The role is in UCL Computer Science's Multi-Sensory Devices Group, whose research covers wearable sensing, robotics, and biomedical devices.

Waymo★3.0 (61)· London

You will use Python, deep learning frameworks (JAX, TensorFlow/PyTorch), and C++ (preferred) to develop data-selection algorithms and scaling laws for foundation model training. The AI Foundations team builds machine learning solutions for autonomous driving, focusing on reinforcement learning, generative modeling, and robust evaluation to improve the Waymo Driver. You will report to a Senior Staff Software Engineer.

JPMorgan★3.9 (20k)· London

You will work with Python, AWS, EKS, Docker, Kubernetes, Kafka, and MLOps tools. As a member of the Applied AI/ML Software Engineering team within CIB Security Services Technology, you will build cloud-based frameworks for hosting machine learning models alongside Data Scientists to integrate AIML solutions into production systems.

Lead engineers use Java, C#/.NET, Python, TypeScript, JavaScript, React, Go, Ruby, Scala, R, and SQL; Git, MacOS/Linux, and CI/CD; and AI-assistive tools. They lead multi-client software consultancy engagements, building and delivering production agentic systems and ML-powered features. The team is typically one to two clients per year.

Deloitte★3.9 (14k)· London

You will work with large language models, prompt engineering, retrieval-augmented generation, orchestration frameworks, and cloud platforms (Azure, AWS, GCP). As a GenAI Solution Design lead in Deloitte's AI Scaling & Transformation team, you design enterprise-grade GenAI solutions for Security & Justice clients in regulated environments. This Senior Manager role involves overseeing delivery across multiple workstreams and leading mentoring delivery teams.

Lead a team of test and DevOps engineers owning CI/CD, Yocto-based embedded Linux, and test automation infrastructure. The role uses Python, C/C++, infrastructure-as-code (Terraform, CDK), and cloud platforms (AWS/GCP/Azure) for a non-invasive neuromonitoring medical device company.

UCL★4.2 (299)· London

Work with Python, PyTorch, JAX, TensorFlow, reinforcement learning, physics-informed ML, differentiable programming, and model-based control. The role is in UCL’s Multi-Sensory Devices Group, researching wearable sensing, robotics, and embodied AI. Develop and evaluate novel methods for accurate trajectory control in complex physical systems.

Sovos★3.3 (105)· London

Design and build Snowflake architecture and dbt model infrastructure for the topline financial data chain (billing, ARR, revenue recognition) at Sovos, a global tax compliance leader. Use advanced SQL, dbt, and optionally Python, Azure/AWS, and MCP to deliver production pipelines that support FP&A, Accounting, and AI consumers through financial close.