Goldman Sachs★3.9 (2.3k)· London

Lead migration of multi-billion-dollar funding trades onto cloud (AWS preferred) and risk-trading platforms for Goldman Sachs’ Corporate Treasury. Work hands-on with traders, quantitative engineers and control functions to build and scale funding-position systems across FX, Loans, Repo and Debt instruments. Provide technical leadership to a global team of engineers.

Morgan Stanley★3.8 (5.4k)· London

You'll work with core Java on UNIX/Linux, Git/Stash, Jenkins, JUnit, REST, TypeScript/Angular, low-latency messaging middleware, KDB/q, and FIX protocol. The role builds, deploys, and supports algorithmic trading strategies, analytical tools, and scalable trading engine infrastructure for automated systems in Equities. As a VP-level Lead, you'll manage multiple functions and guide junior staff.

Work with GNNs, foundation models, active learning, and optimization algorithms using PyTorch or JAX. Drive the core discovery engine of an autonomous laboratory that accelerates materials innovation by bridging simulation and physical experiments.

Work with Java, Spring Boot, Docker, Kubernetes, and message brokers to design cloud-native microservices and event-driven systems. You will lead development of Chip Financial Ltd’s unique Lombard lending platform for its proprietary brand and SaaS clients. Mentor junior engineers in a high-impact fintech environment.

Barclays★3.9 (6.9k)· London

The listing does not specify any concrete technologies, languages, or tools. You will join the Liquid Financing Technology team, building and enhancing data solutions for a modern cross-asset Client Risk platform used by Front Office, Risk, Finance, and Operations teams to monitor exposures, assess risk, and meet regulatory requirements.

You will build Venmark’s AI-platform from scratch using NextJS, Java, TypeScript, and AI-powered workflow automations. The company is an AI-native certification firm transforming the testing, inspection, and certification market by acquiring and integrating traditional providers onto a modern platform. As the first tech hire, you will embed with acquired SMEs across the UK.

Public Sector Resourcing★1.0 (1)· London

Work with Python, AWS, and Terraform to design, build, and maintain cloud-native applications. Support the National Cyber Crime Unit’s mission to disrupt online organised crime by developing AI-driven capabilities and automating operational processes within a multidisciplinary technical team.

Build and operate the distributed systems serving Claude to millions of users, using Python or Rust, Kubernetes, and cloud platforms (AWS/GCP/Azure). The Inference team handles request routing, autoscaling, and fleet orchestration across diverse AI accelerators.

Design complex machine learning evaluation problems that challenge state-of-the-art AI systems, using deep domain expertise in fields such as computational biology, climate science, or robotics. Assess AI-generated ML solutions for correctness, creativity, and methodological soundness, working asynchronously with a global team of researchers and engineers.

You will work with Python, C++, LLMs, deep learning frameworks (TensorFlow, PyTorch, JAX), optimisation methods, reinforcement learning and generative models. The team applies AI to semiconductor design and optimisation while conducting fundamental research for internal use and the scientific community.

Principal researcher role using Python, C++, and frameworks like TensorFlow, PyTorch or JAX, with focus on LLMs, optimization, reinforcement learning and generative models. The research team applies AI to semiconductor design and fundamental research for internal and scientific community. Leadership duties include shaping research strategy and mentoring senior researchers; no team size specified

You will develop predictive ML models for demand forecasting and pricing optimization using Python, scikit-learn, pandas, and GCP. You own the full model lifecycle—design, testing, production deployment—for global retail brands like New Balance and River Island, working alongside the Principal Data Scientist on a lean, expert team.

You will use Python, Trio, PyTorch, TensorFlow, JAX, Kubernetes, Rust, C++, and GPU clusters. The team advances reinforcement learning for large language models, improving Claude’s autonomy, coding, and reasoning capabilities.