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

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.

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.

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 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.

Work with Python (pandas, NumPy) and tree-based machine learning to analyze high-frequency limit orderbook data and build predictive signals for proprietary trading. DV Trading provides liquidity to worldwide markets and hedging opportunities. You’ll collaborate with senior researchers and traders to refine production-ready models.

Research, develop, and evaluate state-of-the-art deep learning models for volumetric CT data using Python and PyTorch. You will contribute to self-supervised pre-training of large 3D foundation models and specialize models for segmentation, classification, and regression to support clinical-trial and real-world evidence programmes. The role is within the Machine Learning function at Qureight, which builds an AI-powered imaging platform for lung and heart disease.

You will use Python with Pandas, NumPy, and FastAPI/Flask to build backend services and APIs. You will also work with SQL, Linux/Unix, and risk analytics platforms to support trading, risk analysis, and trade processing for the front office.

LSEG★3.7 (402)· London

You will use Python (Pandas, NumPy, Scikit-learn), SQL, cloud-based MLOps platforms, and Generative AI/LLM/RAG tools to build predictive models and AI solutions that improve operational efficiency, service resilience, and customer outcomes for LSEG's financial markets infrastructure.

Build scalable backend services and APIs with Go, Python, or C++, and develop frontend applications using React and TypeScript. You will ship AI-powered product features end-to-end on a platform combining computer vision, multimodal AI, and real-time data. Work closely with AI and platform engineers on new capabilities within a small, experienced team.

You will work with C++ (including memory management) and Python (Pandas, NumPy) to build high-performance infrastructure, data pipelines, and quantitative trading systems. The team develops and optimizes simulation and backtesting tools and handles high-volume market data feeds.

Work with C, C++ or Rust, Python, computer vision models (object detection, tracking), state estimation and sensor fusion (Kalman filtering, factor graphs, SLAM). You will own integration of a new counter-UAS initiative, building a prototype from concept through trials. This role spans robotics, ML and systems engineering.

You will use Adobe Creative Suite (Photoshop, Premiere Pro) and Canva for graphics and video, and manage social platforms (LinkedIn, X, Instagram, YouTube, TikTok) with scheduling and analytics tools like Hootsuite, Buffer, or Sprout Social. You will own Ultralytics' social media strategy, creating content to showcase its YOLO AI models and vision AI advancements, and collaborate with Engineering and Marketing teams on product launches and announcements.