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.

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.

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

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.

Build enterprise-grade web applications using Python (Django/FastAPI), React, TypeScript, and PostgreSQL. Develop RESTful APIs, responsive UI components, and contribute to system design, CI/CD pipelines, and performance optimization.

You’ll work with Python (Django/FastAPI), React, TypeScript, PostgreSQL, REST APIs, and CI/CD. You’ll own end-to-end feature delivery on scalable, enterprise-grade web applications.

Work with Python, DevOps, Linux, Pandas, NumPy, and relational/non-relational databases. You'll join the Vendor Data Group at a global quant firm to build and maintain mission-critical ETL/ELT data integration pipelines and tools for alternative commodity and macro data, collaborating with a trading team.

Develop end-to-end solutions in Python (pandas/numpy) for the Commodities RAD team, building data, research & trading platforms and tools for Portfolio Managers. Also use React/Angular for web frontends and SQL for databases.

Working with Core Python, Pandas, NumPy, Flask/FastAPI/Django, SQL, and Unix/Linux, you will build backend applications and data processing pipelines for trading and risk management within an investment banking environment, supporting risk calculations, trade workflows, and reporting.

Imperial College London★4.2 (238)· London

Work with PyTorch, GPU kernel programming, Verilog, and NVIDIA's Holoscan Sensor Bridge to integrate FPGA-based AI-ISP accelerators with edge GPU platforms. The project targets low-latency, high-throughput sensor-to-GPU streaming for the "Sense-Decide" pipeline in edge automation.

You will build and maintain Python services using FastAPI and Azure Functions, design and consume REST APIs, work with MS SQL Server, and leverage Azure infrastructure. The team delivers a loan management platform for a global financial services firm, handling complex servicing workflows in a regulated environment.

Edited★2.7 (3)· London

You will work with Python, *nix, LLMs, MCP, Django, Flask, FastAPI, Elasticsearch, and SQL databases. You will build an AI chatbot with agents and tooling, and scale a large-scale retail data infrastructure on AWS and bare metal for the company's AI-driven retail intelligence platform.

Cboe Global Markets★3.7 (14)· London

You'll work primarily with Python to design and build highly reliable trading systems, working closely with advanced SQL, Linux, and optionally PostgreSQL, Snowflake, Apache Kafka, Apache Airflow, Django, Flask, or FastAPI. You'll expand data pipeline and event streaming functionality for Europe's largest equities exchange and related platforms, while leading complex projects, mentoring developers across multiple global teams, and participating in production support for Cboe Europe's trading operations.

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.

Bloomberg★3.8 (1.1k)· London

You will work with Python, SQL, PySpark, Pandas, NumPy, Airflow, dbt, Kafka, Iceberg, Trino, Superset, and data visualization tools. The Entity Data team manages core entity data for over 7 million public and private companies, supporting reference data and private markets; as Data Quality Manager you define and execute the quality strategy.

Wolf & Badger★3.0 (3)· London

Senior Product Manager — Wolf & Badger. Work with AI agents, LLMs, APIs, MCP, commerce and integration platforms, plus structured product data, payments and fulfilment infrastructure. Own the product strategy for the agentic-commerce platform that powers the marketplace’s distribution channels, retail media, brand integrations and partner connectivity. You will be the sole product manager on this remit, working with a team of c.10 engineers and the VP Technology.

Prima★3.6 (45)· London

You'll work with Kafka, Flink, Spark, Databricks, Python, AWS, Redshift, PostgreSQL, and DevOps/CI-CD tools to build data products and pipelines for Prima's pricing and underwriting domain. The role bridges machine learning and engineering, focusing on data architecture, transformation, governance, and enabling teams to ingest, store, and serve data products. You'll join over 350 engineers across Prima, an online motor insurance provider trusted by 5 million drivers expanding in the UK and Spain.

Design, build, and deploy quantitative models using Python, R, and libraries (numpy, pandas, scikit, pytorch, tidyverse, caret, ggplot) plus NLP tools, SQL, AWS, Sagemaker, DataBricks, Snowflake, MLFlow, and Weights & Biases. The team creates systematic country risk analytics and ML/NLP pipelines for BMI’s market insights, supporting clients in risk assessment.

Work with Python, Pandas, NumPy, Scikit-learn, SQL, LLMs, RAG, and MLOps to design, build, and deploy enterprise-scale AI/ML solutions improving operational efficiency, service resilience, and customer outcomes at LSEG, a global financial markets infrastructure and data business.

Senior Python Developer role building trading and risk platforms using Python, SQL, Pandas, NumPy, Flask/FastAPI/Django, PySpark, Unix/Linux shell scripting, and enterprise platforms like Quartz or SecDB. The team develops backend services, data pipelines, and risk applications for trade lifecycle, risk calculations, and regulatory reporting within investment banking.

Python, FastAPI, PostgreSQL, GCP, Docker, Terraform. The team builds Scenario Builder, a platform for energy-system modelling, grid planning and decarbonisation analysis. You will lead a hands-on squad of 3–5 engineers, staying close to the code while setting technical direction.

Python and SQL for computer‑vision projects using Vision Language Models (VLMs) at a tech start‑up. You will work on a broad range of machine‑vision tasks, blending research, implementation, and support from a team of PhDs and MScs.

The role involves designing and implementing machine learning tools, web applications, and database management platforms, plus developing AI algorithms for ophthalmic image segmentation and analysis. You will work with the AI and Data Science team at Moorfields Eye Hospital’s NIHR Clinical Research Facility, which delivers ophthalmology clinical research and AI-driven diagnostic models for eye diseases.

You will work with Python, Django, Django REST Framework, FastAPI, PostgreSQL, AWS, React.js, Docker, Redis, Celery, Pandas, NumPy, Git, Jenkins, Elasticsearch, and Kubernetes, using AI tools like Claude Code and Cursor. You’ll shape the technical direction of a cloud-based property management platform handling payments, quoting, invoicing, booking, search, data pipelines, notifications, and fraud prevention. This is a leadership role bridging product vision and technical execution, guiding engineers toward delivery.