You'll work with Python (pandas, OOP), SQL (PostgreSQL, Snowflake), CI/CD pipelines, Git, and GitHub. You'll develop and support in-house fund management tools that assist Fund Managers in managing funds for Legal & General's asset management division.

JPMorgan★3.9 (20k)· London

You will work with Java, TypeScript, React, Scala, SQL and No-SQL databases on cloud-native platforms. As part of JPMorganChase’s Data Platforms team within the Chief Data & Analytics Office, you will engineer solutions in metadata, meta-modelling, distributed systems, domain-specific languages and interpreter design. You will provide technical guidance to the team.

Deliveroo★3.3 (1.5k)· London

Build production infrastructure for Generative AI at Deliveroo and DoorDash, leading design and architecture for real-time GPU serving, high-throughput batch inference, and fine-tuning (SFT/DPO/LoRA) of open-weight LLMs and VLMs. Own the LLM Gateway, Agent Gateway, evals infrastructure, guardrails, and cost attribution, while mentoring engineers and setting technical direction for a small, high-leverage centralized GenAI platform team.

You will work with AWS, Kubernetes, Terraform, and observability tooling like Datadog to handle platform requests and incidents. As a member of a new Platform Support Engineering team, you will be the primary contact for engineering interactions across global clients on a 24/5 basis, owning investigations and improving tooling and processes.

You will deploy ML models and engineering surrogates (e.g., deep learning on CAE/CFD/FEA data) to production environments, using Python, PyTorch, Pandas, fastAPI, Scipy, and Kubeflow. PhysicsX builds an AI-driven simulation software stack for engineering and manufacturing.

Wise★3.5 (42)· London

You will work with Python, dbt, Airflow, Kafka, and Trino/Iceberg to build high-volume streaming and batch data pipelines. You will serve as the data architecture lead for the Marketing Platform team, building the data infrastructure that powers Wise’s global customer acquisition channels.

JPMorgan★3.9 (20k)· London

Lead Scala/Java Software Engineer on the Data Platforms team within JPMorgan Chase’s Chief Data & Analytics Office, leading an agile team to build scalable, secure technology products. Works with Scala, Java, Cats Effect, SQL/No-SQL databases, and AI-assisted development tools, focusing on metadata, meta-modelling, distributed systems, and domain-specific language design.

Lead Cloud Engineers at Made Tech use AWS, Azure, GCP, Terraform, CloudFormation, Docker, Kubernetes, CI/CD, and languages like Python, Bash, and JavaScript. They help public sector organisations design, implement, and maintain secure, scalable cloud infrastructure. The role includes line managing and mentoring junior colleagues.

JPMorgan★3.9 (20k)· London

Senior Lead Software Engineer role on JPMorgan's Data Platforms team in the Chief Data & Analytics Office, working with Scala, Java, Cats Effect, and cloud-native technologies. The agile team builds secure, scalable technology products spanning metadata, meta-modelling, and distributed systems, with a focus on AI-assisted engineering and domain-specific languages.

You will use AWS, AWS Glue, Apache Airflow, Snowflake, Amazon QuickSight, SQL, and Python to build and maintain production ETL/ELT pipelines and cloud-native data platforms. You join a newly established Data Engineering team within a leading UK Financial Services organisation focused on unsecured lending.

You will build and scale a payments platform processing 100 currencies and a discovery engine for independent tourism businesses using Svelte, TypeScript, Python (FastAPI/Django), PostgreSQL, and AWS. You join a profitable, lean team of nine as one of the first engineers.

Atlassian★3.9 (61)· London

Leading a distributed EMEA team, you'll use Python, JavaScript, APIs, and microservices to build AI-powered solutions with generative AI, LLMs, and agent-based frameworks. The Forward Deployed Engineering team partners with top organizations to solve complex problems using Atlassian’s AI capabilities.

Too Good To Go★3.7 (14)· London

Spring Boot, Java 25, Kubernetes, AWS, React.js, TypeScript, Kotlin, and Swift. You will build and lead a new London engineering hub, delivering integrations and systems that power workflows for a marketplace app fighting food waste. As the founding Engineering Lead, you will recruit and manage a multidisciplinary team from the ground up.

Junior C# and ASP.NET developers will use SQL, .NET Core/Framework, JavaScript and Azure to build a centralized SaaS platform for FX payments, helping financial institutions manage compliance, costs and cashflow.

You will work with Azure, Adverity, SQL, Python, cloud services (Azure, GCP, AWS), data orchestration tools (Airflow, Prefect), Git, and visualization tools (Power BI, Tableau, Datorama). As a data engineer in a media activation team, you will build and maintain ETL pipelines and reporting platforms to deliver marketing intelligence for clients.

You'll work with Python, C++, Rust, embedded systems, and commercial liquid handlers from Opentrons, Hamilton, Tecan, and Beckman, designing thermal control, liquid handling, and motion subsystems. As first engineering hire at Amplisynth, you'll lead development of their DNA synthesis automation instrument from concept to deployment, working with founders and later building the engineering function.

You will work with Python (Django/FastAPI), TypeScript, React, Astro, Svelte, PostgreSQL, AWS, Terraform, and frontier AI models via Amazon Bedrock. You'll own technical direction, mentor engineers, and build AI products for UK public services in health, education, planning, and Parliament. The role is in small, empowered, cross-functional teams.

You'll work with Python, PyTorch, SGLang, large language models, embeddings/reranking models, PEFT/LoRA, RAG, prompt engineering, Git, Docker, microservices, and cloud infrastructure. The early-stage company builds AI-powered products transforming specialised financial markets, combining machine learning with real-world trading workflows. You'll collaborate with a small engineering team, founders, brokers, and traders on commercially impactful systems.

The role uses SQL, R, and/or Python for advanced statistical modeling, machine learning, and psychometric analysis. It is part of the Talent Insights and Analytics function at EY, where you design and conduct organizational research to inform strategic talent decisions and workforce interventions.

Working with Python, C++, and deep learning frameworks such as TensorFlow, PyTorch, or JAX, the role covers LLMs, deep learning optimization, reinforcement learning, and generative models. The research team applies AI to semiconductor design and optimization, alongside fundamental research supporting internal applications and the broader scientific community.

You’ll implement ML research ideas using Python or C++, alongside deep learning frameworks like TensorFlow, PyTorch or JAX. The team applies AI (including LLMs, reinforcement learning and generative models) to semiconductor design and fundamental research.

You'll design, build, and maintain scalable AI data pipelines, cloud-native backend systems, and distributed services using Python, REST APIs, and microservices with FastAPI, Flask, or Django. You'll productionise Machine Learning, NLP, and Generative AI models, work with SQL databases, AWS/Azure, Docker, and Kubernetes, and mentor juniors. The company specialises in AI and data engineering, transforming AI research into production systems.

You will work with Python and large language models (LLMs) to build AI solutions and AI agents. The company develops cutting-edge AI products for clients, with a focus on innovation and creative freedom.

You'll build production-ready machine-learning systems in Python, applying deep learning and data-pipeline work to model human behaviour at scale for a London AI startup. The role turns unstructured human data into accurate, commercially viable population simulations, requiring high autonomy to ship fast, high-quality solutions.

As a Node.js/TypeScript Engineer in Sainsbury's Martech domain, you'll work on the Multichannel Messaging Hub (MMH) team using JavaScript, TypeScript, Node.js, microservices, Kafka, Snowflake, Kubernetes, AWS Serverless, and Terraform. The team orchestrates campaign delivery across email