You'll use Python, SQL, shell scripting, containerization, infrastructure-as-code tools, and Scala/Java or Python to build and maintain scalable data pipelines. You'll support a financial technology company's data infrastructure, contributing to AI/ML experiences and international applications. No team size is stated.

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 Python Developer role using Core Python, Flask, VueJS, JavaScript, CSS, HTML, SQL, AWS, Terraform, Docker, and serverless components, with CI/CD and Agile practices. The developer builds, enhances, and supports production applications within UK public sector programmes, collaborating with delivery, product, and data teams.

Trainees will learn Linux, Git, Docker, AWS, Azure, Google Cloud, CI/CD, and Infrastructure as Code. The program provides structured training and practical DevOps projects to build a portfolio. No prior experience is required.

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.

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.

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.

DeepL★3.8 (4)· London

Work with Kubernetes, Terraform, ArgoCD, Go or Python, and AWS across hybrid on-prem and cloud infrastructure. The Hybrid Platform Engineering track builds and operates the compute layer—Kubernetes control plane, networking, storage, and core services—powering DeepL's language AI products and research. The role involves deepening the hybrid model and unifying workloads across on-prem and AWS.

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.

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.

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.

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.

Java back-end developer using microservices, REST APIs, AWS (Lambda, EKS, RDS, S3, MSK), CI/CD, and AI tools (GitHub Copilot, LLMs). Builds next-gen trading and cash management systems for the Short-Term, Cash, and Collateral desks, modernizing platforms and migrating to AWS.

Java 11+, Spring Boot, microservices, event-driven architecture, Terraform, and cloud platforms (Azure, AWS, or GCP). The team builds post-trade technology solutions including business-critical applications, APIs, client reporting platforms, and web portals for capital markets. You will mentor developers and contribute to architectural decisions.

Work with AWS, Kubernetes, Terraform, Python, and IaC tools. Build and scale a critical AWS platform used across a bank, improving platform stability through new technology and processes.

Lead DevOps Engineer: work with AWS, Azure, GCP, Terraform, Linux/Unix, Python/Go/PowerShell/Nodejs/C#, and CI/CD tools (Octopus/TeamCity/Jenkins/Azure DevOps). Role is at a tech consultancy building and running cloud infrastructure, automating deployments with IaC, and managing a team of engineers.

You will work with AWS, Kubernetes, Terraform, Python, Java or Scala, and AI-driven development tools (Claude, LLMs). You will build and maintain the distributed-compute and data-science platform that powers Macquarie's trading and analytics workflows, collaborating with quantitative analysts and trading desks.

Work with Terraform, Ansible, Kubernetes, Python, Bash, Go, Jenkins, GitHub Actions, Prometheus, and Grafana to build infrastructure automation platforms supporting python-based quantitative research and trading systems. Manage on-premises resources across Ubuntu and Windows Server environments.

Builds cloud platforms for a systematic quant hedge fund's trading and research, using AWS (EC2, S3, VPC), Python/Bash, Jenkins/GitLab CI, Terraform/CloudFormation/AWS CDK, Docker, and Kubernetes to support digital asset and crypto systems.