Monzo★3.5 (108)· London

You will build and deploy deep learning, graph-based, and sequence-based ML models using Python and SQL, with exposure to Go. You will design human-in-the-loop systems and autonomous agents to route, prioritise, and automate customer-support issues for millions of customers across thousands of support staff at Monzo. You will be one of four ML engineers embedded in product squads.

Python, PyTorch, Ray, distributed systems, cloud and GPU infrastructure. You will build platforms and services supporting ML training and deployment, develop tooling for data processing and model lifecycle, and maintain distributed systems for a well-funded AI company.

As the first dedicated product engineering hire, you’ll build the platform layer using Python, FastAPI, React, and modern TypeScript, with expert SQL and data modeling. You’ll develop full-stack features, architect auth/permissions/APIs for multi-tenant workspaces, and translate AI workflows into clear interfaces for OpenHuman’s high-stakes decision-making platform.

Build full-stack applications using Python, React, and TypeScript at an elite fintech firm. You will develop backend services, APIs, and microservices, plus build real-time trading dashboards, analytics, and data visualisation tools for traders and quants.

Work with React, TypeScript, and modern frontend technologies to build real-time trading dashboards, data-rich UIs, and reusable component libraries for an elite FinTech firm's high-performance trading environment.

You'll work with Python, LLMs for post-training (RL, fine-tuning, distillation), distributed training, and inference optimisation. This YC-backed AI startup builds frontier systems modelling complex large-scale real-world behaviour. As a Research Engineer, you'll own the path from research to production, working directly with the CEO and Head of Research.

You'll build backend infrastructure and classical ML pipelines for a logistics platform that tracks inventory, flags supply gaps, and optimises tactical routes for armed forces. Work involves on‑prem deployment on constrained hardware (16–20 CPUs, 64GB RAM) and integration with legacy command‑and‑control systems. You join a small team of six.

You'll use Python daily, with KDB and SQL useful. You'll build a Vol Alpha library for equity-derivatives volatility strategy development and backtesting, working with portfolio managers on dispersion and relative-value strategies. You'll join a new specialist team of engineers, quants and data scientists.

This Head of Machine Learning role works with ML, search, personalisation, Generative AI, LLMs, deep learning, recommendation engines, and ranking algorithms. The team builds and scales high-throughput, production-grade ML systems for personalised digital retail experiences, directly shaping customer engagement and commercial performance. They lead a team of ML specialists within the Product, Data & Technology organisation.

This CTO will lead a digital platform built with Ruby on Rails, working with APIs, data, infrastructure, Stripe, and CI/CD tooling. The company operates a subscription-based digital platform with a recurring-revenue model and is scaling its product. Currently leading approximately 15 outsourced specialists, you will build and manage a high-performing in-house engineering team.

Allianz★3.8 (3.4k)· London

Use catastrophe modelling platforms, Power BI, Excel, VBA, and SQL for portfolio steering and CAT analytics. The Marine team performs strategic portfolio monitoring, natural catastrophe and terrorism modelling, accumulation management, and reinsurance-related analytics to support underwriting.

You'll build with React, TypeScript, Java, and Python, working across the frontend and API layers for an AI operating system for drug discovery. You will own the scientist-facing product surfaces, trust/provenance interfaces, and frontend architecture at a stealth startup of roughly a dozen people.

Build and maintain the company’s platforms using JavaScript, Node.js, Next.js, Express.js, React/React Native, .Net 4.8/9/10, C#, HTML/CSS, and API Restful Services. You will develop both web and mobile applications, collaborating with the team while working independently.

Python, LLMs/GenAI, and AWS/GCP/Azure are used to build and deploy production-grade machine learning systems for an AI-native platform that automates complex workflows at scale.

You'll work with Python and/or TypeScript, using full-stack JavaScript or backend Python. The role is a founding engineer at a stealth AI company backed by a £100M bootstrapped founder with three successful exits.

Linux Recruit★3.0 (1)· London

Work with PyTorch, distributed training libraries, Slurm, Kubernetes, and AWS multi-node GPU clusters to architect and optimize large-scale model training pipelines. You will join a stealth AI startup at the intersection of robotics and embodied AI, building the infrastructure that powers next-generation AI breakthroughs.

Google★4.3 (6.2k)· London

This role uses Google Cloud Platform (GCP), Vertex AI, Gemini models, LangGraph, CrewAI, and ADK to build agentic workflows, MCP servers, and RAG-like architectures. You embed with strategic customers to code, debug, and ship production-grade GenAI solutions, addressing integration, data readiness, and state-management blockers. You also build evaluation pipelines and observability frameworks while co-building with customer engineering teams.

McKesson★3.5 (7.7k)· London

Senior Data Engineer: Snowflake, dbt, Airflow, ADF, Python, Databricks, Azure, AKS, Infrastructure as Code, CI/CD. You will own and build the ClarusONE data platform, designing scalable pipelines and establishing engineering standards for reliability, security, and compliance.

Lead Engineer role: work with Python, TypeScript, Go, and cloud infrastructure (AWS/GCP/Azure) to build AI agents that automate manufacturing tasks like RFQ estimating and production planning. You will lead a small engineering team, own technical design, and integrate with ERPs, email, and spreadsheets.

As a Staff Software Engineer, you will architect public APIs and document pipelines using Python, AWS, and Terraform for a neurosymbolic platform that combines LLMs with symbolic reasoning for regulated financial and compliance sectors.

You will work with Azure, Microsoft Fabric, SQL, cloud data platforms, and AI/ML frameworks. Leading a multidisciplinary Data & Engineering function, you'll own platform strategy, architecture, engineering standards, and delivery, building teams across Data Engineering, Software Engineering, and Client Data Solutions. The company is a specialist technology business delivering data-led solutions to enterprise clients.

You'll work with GCP (Cloud Run), Terraform, Ruby on Rails, Go, PostgreSQL, Kafka, PubSub, CI/CD, and agentic AI systems (LLMs, context engineering, agent orchestration). You'll build and own the internal platform (infrastructure, CI/CD, observability, golden paths) and weave AI into

Lead the evolution of a high-growth AI-powered creator platform at Fanvue, serving tens of millions of users. Architect a monolith-to-event-driven services transition using TypeScript, Node.js, Go, and AWS. Build AI infrastructure — embedding pipelines, vector stores, and LLM orchestration — for automated chat and content discovery, and optimize PostgreSQL for high-throughput workloads.

Software Engineer role using Python, SQL, ETL pipelines, Data Lakes/Lakehouses, distributed systems, microservices, Excel add-ins, CI/CD, and observability tools. You'll build a medallion architecture data platform for a Hedge Fund, working on data engineering, infrastructure, and frontend in a small collaborative team.

You'll work with Adobe Creative Suite (Photoshop, Illustrator, InDesign, After Effects, Premiere Pro), Figma, and AI tools like ComfyUI and Midjourney. You'll lead end-to-end creative production for marketing, event, and digital assets at Ultralytics, turning complex vision AI into clear visuals for the company that creates the leading YOLO AI models.