MAREX★3.2 (6)· London

Risk Data Analyst at Marex works with the Data Platform, Power BI, and structured/unstructured datasets. The role bridges Risk and Technology, supporting data-led risk management, monitoring, and reporting across disciplines like market, credit, and operational risk.

Work with TensorFlow or PyTorch, Python, and related computer vision/graphics libraries on neural network architectures (convolutional, recurrent, transformer, diffusion-based). The Visual Computing Group (VCG) researches and develops generative models for game rendering and live video streaming to advance state-of-the-art runtime efficiency, visual quality, and latency.

You will build AI agents using Python, SQL, Docker, Kubernetes, AWS (RDS, EKS, S3), GitHub Actions, RAG pipelines, BM25, vector search, hybrid retrieval, and knowledge graphs. These agents interpret geopolitical and financial signals for Kharon, a company providing global security risk intelligence.

You will build scalable server-side logic using JavaScript, TypeScript, and Node.js in a microservices architecture on AWS with Kubernetes, Terraform, Kafka, and Snowflake. You will join the MMH team within the Martech domain, which orchestrates campaign delivery across email, push notifications, and personalised content for all Sainsbury’s Group brands. The team includes 7 engineers.

You'll use Java, Kafka, Flink, SingleStore, HDFS/S3, and Scala to build high-performance, low-latency data systems. The Data Platform team in Global Markets owns the post-trade stack, processing high volumes of data and developing an AI-powered analytics UI/agent framework.

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.

Goldman Sachs★3.9 (2.3k)· London

Build a high-performance, low-latency data platform for post-trade processing using Java, Kafka, Flink, SingleStore, HDFS/S3, and Scala. You will own the full lifecycle of core systems, designing distributed computation and an AI-powered UI/agent framework to deliver intelligent analytics over large-scale business data.

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

Virtusa★3.7 (1.1k)· London

Work with Snowflake, DBT, Python, SQL, and AWS services to build enterprise data platforms. The role supports a global pharma engagement, designing scalable data solutions for advanced analytics, clinical insights, and business intelligence.

Snowflake, DBT, Python, SQL, and AWS. Leads architecture of enterprise data platforms for a global pharma engagement supporting clinical insights, business intelligence, and data governance.

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.

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.

You will configure and maintain Workday, Greenhouse, CultureAmp, Kyriba, FloQast, and Workato, using Claude Code and agentic AI tooling. As an associate cross-platform engineer on the Finance & People Technology team, you support the SaaS estate underpinning finance and HR at a global alternative investment management firm.

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.

Work with C#, Python, Java, SQL, and AWS (ECS, S3, DynamoDB) to design, build, and maintain TradingHub’s market data environment and analytics. Collaborate with Pricing Quants and Risk Strats to productionise financial markets data for the company’s trade surveillance software.

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.

You will work with AWS cloud data platforms including S3, Glue, and managed ETL services, using SQL and Python to design ETL/ELT solutions for extracting value from large-scale data. This role is for a Data Engineer at Third Nexus Group Limited.

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'll work with TypeScript, Node.js, AWS serverless technologies (Lambda, SQS, EventBridge, API Gateway), MongoDB, Terraform, and GitHub Actions. Seccl is an embedded investment platform helping people invest better, owned by Octopus. You'll design and operate services within cross-functional squads, mentor engineers, and support regulated investment operations in a build-and-run model.

JPMorgan★3.9 (20k)· London

You will work with Python, AWS, EKS, Docker, Kubernetes, Kafka, and MLOps tools. As a member of the Applied AI/ML Software Engineering team within CIB Security Services Technology, you will build cloud-based frameworks for hosting machine learning models alongside Data Scientists to integrate AIML solutions into production systems.

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.