Design, build, and operate a Kubernetes-based MLOps platform using Helm, Terraform, Kubeflow, KServe, vLLM, and JupyterHub. The platform supports the full model lifecycle—experimentation, deployment, and scalable inference—for AI, ML, and LLM workloads in production.

You'll build and operate a Kubernetes-based AI/ML platform using Helm, Terraform, Kubeflow, KServe, vLLM, and JupyterHub. This role focuses on creating infrastructure, tooling, and guardrails so MLOps and data science teams can reliably deploy and serve models at scale.

You will work with AWS, Python, SQL, ETL/ELT pipelines, data warehousing, and APIs. You will own the data platform for a company developing AI and machine learning products that help enterprise clients make decisions. You will start as a senior individual contributor with the opportunity to build and lead a future data team.

Lead TypeScript and Python development, CI/CD, and API-first design to embed AI into production software platforms. You will modernize legacy systems toward service-based architectures and guide integration with AI services like MCP, working across DevOps, platform engineering, and data science teams.

You will work with backend development, databases, APIs, cloud services and production machine learning systems. This is for a growing technology business. No specific project or team size is mentioned.

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.

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.

Cint★3.5 (13)· London

Use Python and SQL for statistical modeling and machine learning to optimize Cint's programmatic research marketplace (Cint Exchange). You will analyze marketplace dynamics, conduct A/B tests, and build predictive models to guide product and pricing strategy.

You will build and evolve customer-facing interfaces for AI Virtual Agents using React, TypeScript, Next.js and Vite, and refactor the frontend into a scalable platform with a shared component library and design system. Unitary’s factory builds custom operations agents that complete complex workflows end-to-end in customer tools.

Samsara★3.6 (32)· London

Samsara interns work on the Connected Operations Cloud, building backend infrastructure in Golang, web clients with TypeScript/React and GraphQL, mobile with React Native, or embedded software for IoT devices. Projects involve scaling data ingestion, real-time data processing, and creating actionable insights for industries like transportation and agriculture.

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.

Hudson River Trading★4.5 (2)· London

You will use Python, C++, Pandas, NumPy, R, or MATLAB to build and maintain predictive trading models. As an algorithm developer, you research and test novel order execution and model training methods, applying

Hudson River Trading★4.5 (2)· London

You will work with Python, Pandas, NumPy, R, and MATLAB to apply statistical analysis and machine learning to vast quantities of market data. The team builds and maintains predictive trading models for the company's high-performance trading infrastructure. You will research, develop, and test order execution methods to increase trading efficiency.

BNY★3.5 (5.5k)· London

You'll use Java 17/21 with Spring, Maven, Groovy, JavaScript/TypeScript (Angular), Docker, GitLab CI/CD, IntelliJ, Windsurf, Splunk, and AppDynamics to build secure backend services, batches, and APIs for a global financial services company.

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

Lovable★4.0 (43)· London

Uses Go, Rust, TypeScript; AWS, Azure, Google Cloud, Cloudflare; Kubernetes, Terraform, Temporal, OTEL, CI/CD; PostgreSQL, ClickHouse, Firestore, Spanner, BigQuery. Builds the platform for Lovable Enterprise enabling secure, cloud-agnostic deployment, defining architecture for sandboxing, networking, encryption, identity, and mentoring engineers.

Zoopla★3.9 (18)· London

A 12-month maternity cover role on a dual-stack C#, .NET, and TypeScript backend with React microfrontends, using AWS managed services (ECS/Fargate, Lambda, SQS, DynamoDB, DocumentDB) and Terraform/SST. You'll build B2B SaaS software for estate agents and home builders at Alto Software Group. Take end-to-end ownership of features from design to production, working with the product team and AI coding agents.

You'll work primarily with TypeScript, Node.js, and PostgreSQL on GCP, designing and building scalable backend systems. The team develops and maintains a robust investment platform that powers features like mutual funds, bonds, and family investment tools.

DeepL★3.8 (4)· London

You'll work with C# / .NET, RESTful APIs, distributed architectures, and optionally React/TypeScript, plus MCP, CLIs, OAuth, and AI coding tools. You join the API Enterprise team, which builds enterprise adoption features (usage insights, cost controls, RBAC, compliance, data residency) for DeepL's Language AI API platform.

Quantitative Researchers at Jane Street build models, strategies, and systems for pricing and trading financial instruments, working with Python, petabytes of data, and a large GPU cluster. They apply statistical and ML techniques, from linear models to deep learning.

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.

Backend engineers use Python, Django, Django-REST-framework, GraphQL (Graphene), Celery, Postgres, and AWS (Packer, Consul, Terraform). They build and maintain the AI-driven energy management platform that powers utilities and optimises renewable generation. The global engineering team is around 1,400 people.

Wise★3.5 (42)· London

You will build and refine financial crime prevention systems using Java (or JVM languages) with Spring, React/JavaScript/TypeScript, and CI/CD pipelines, working 80% backend and 20% frontend. You join the Account Integrity team, which protects Wise’s global platform against fraud via machine learning and real-time transaction monitoring, and you will own projects end-to-end.

You’ll train ML models, work on ML libraries and workflows, and use a GPU cluster with H100/H200/B200s. Projects are real-world machine learning applications for Jane Street’s global trading business, testing ideas against noisy financial data. No team size is stated.

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.