Hudson River Trading★4.5 (2)· London

You will write and maintain critical trading infrastructure using C/C++ or Python on Linux, working closely with engineers who design trading algorithms in a fast-paced, real-time environment. The role is with Hudson River Trading, a firm that brings a scientific approach to trading financial products.

Amazon★3.5 (56k)· London

Develop generative AI and large models using Java, C++, Python, and Unix/Linux for Prime Video’s observability team, which combines log management, tracing, and AI-powered analytics to detect and diagnose issues at unprecedented speed.

You will use Python, C++, Linux/UNIX, PyTorch, JAX, or TensorFlow to develop and deploy advanced ML models (Deep Learning, Reinforcement Learning, sequence models) for forecasting asset volatility. Part of a specialized research team, you will perform greenfield research on unstructured datasets to discover new alpha signals for trading at a systematic investment firm.

Millennium Management★3.8 (21)· London

You will write clean, well-tested Java and Python code. You will build and run platforms that produce the firm’s official VaR, stress, and risk analytics, and develop AI-powered risk tooling, including agents and plugins connecting LLMs to risk data.

You will work with Python (Xarray, Dask, Rasterio), geospatial data formats (NetCDF, Zarr, GeoTIFF), UNIX shell, and Docker to develop climate and nature risk models and analytical tools for ISS Sustainability's Climate & Nature Solutions unit. The role involves building datasets, applying machine learning and statistical methods to assess physical climate risks, and supporting financial market participants and governments in understanding climate-related investment impacts across all asset classes.

BlackRock★3.8 (632)· London

Build and maintain equity risk models using Python within the Aladdin Financial Engineering team, which develops financial models for risk management analytics used by BlackRock and its clients. This role also contributes to applying AI and automation to modernize workflows.

Checkout.com★3.8 (15)· London

Data Scientists at Checkout.com use Python, ML algorithms (supervised learning), feature engineering, statistics, and LLMs to develop models and estimators that boost payment acceptance rates for a portfolio of merchants. The role collaborates with Product, Engineering, and other Data Scientists to productionise ML features and build evaluation/monitoring frameworks.

Design, optimise and operate high-performance Linux-based compute infrastructure. Work with distributed computing, parallel processing environments and tools such as MPI, OpenMP, CUDA and Slurm. Program primarily in Python, C++, C, Rust or Fortran on computationally intensive projects.

Work with modern C++, Python, Perl, Shell scripting, SQL, and machine learning libraries; also CUDA/GPUs, TCP/IP, UDP, git, and Linux/Unix. You will develop algorithmic trading solutions for financial markets at Jefferies.

Nebius★0.0· London

You'll work with Go, Python, or C++, Kubernetes, Docker, Terraform, and Ansible to ensure fault tolerance and scale for Nebius's full-stack AI cloud platform that handles GPU orchestration, model training, and inference optimization. You'll implement CI/CD processes and solve infrastructure problems across compute, storage, and networking for a company building AI cloud infrastructure for developers and enterprises globally.

Nebius★0.0· London

You'll work with Java, Kotlin, Go, Python, and Ruby to maintain DevTools' massive-scale CI/CD infrastructure: 25k daily builds in TeamCity, 100 TB of artifacts in Artifactory, and a monorepo in GitLab comparable to FAANG systems. The SRE team modifies GitLab and TeamCity plugins, experiments with RAG setups, and focuses on understanding user problems, defining metrics, and improving system performance and reliability. This role requires a 50/50 blend of SRE and SWE experience with deep Unix and JVM knowledge.

Nebius★0.0· London

You'll work with server hardware, firmware, network equipment, and Unix/command-line systems to solve complex infrastructure issues across Nebius's global AI cloud datacenters. The role involves troubleshooting, hardware problem management, collaborating with R&D on design improvements, and traveling to datacenters for large-scale projects. You'll act as a subject matter expert and help develop processes and training materials for the IT hardware team.

You'll work with Python, ML models, AWS infrastructure (Terraform/CloudFormation), and microservices to design and test AI-powered algorithms for Xapien's due diligence and risk intelligence platform. The company combines AI with speed and scale to help organisations conduct faster due diligence across financial services, wealth management, and supply chain sectors. This graduate role involves close collaboration with the product team to refine algorithms and requires autonomous problem-solving in a fast-paced environment.

You'll design and manage on-premise Kubernetes infrastructure using Prometheus, Grafana, and distributed tracing, plus build MLOps platforms and secure multi-tenant clusters with policy-as-code governance. The role involves scripting in Python, Go, Rust, or Bash; GitOps workflows; CNCF ecosystem tools like Helm and ArgoCD; and infrastructure-as-code with Terraform and Ansible. Helsing is a defence AI company developing AI systems for democratic nations, operating in high-security on-premise environments across European offices.

Hudson River Trading★4.5 (2)· London

This distributed compute engineer role at Hudson River Trading focuses on building and optimizing the research cluster infrastructure powering the firm's algorithmic trading strategies. You'll work with C++, Python, Linux systems, and in-house or open-source tools to manage resource scheduling, data caching, job monitoring, and workload optimization while collaborating directly with quantitative traders and engineers across trading teams.