C++ developers will work on ultra-low-latency exchange protocol encoders and automated trading strategies, using C++ and optionally Python, for a data-driven prop fund’s global automated trading systems. The role involves collaborating with researchers and ops in a small, fast-paced team operating in a real-time environment.

Lead 6-7 engineers on core ML infrastructure for a systematic quant fund: distributed model training, LLM hosting/fine-tuning, and scalable deployment. Use Python with working knowledge of C++/Java. Own technical direction for real-world, high-stakes systems.

You'll work with Python, NLP/LLMs, SQL/NoSQL databases, and cloud infrastructure, designing retrieval, knowledge-base, and reasoning models. You own projects end-to-end at Catapult, which builds personalised AI that understands a user's full work context across email, calendar, Slack, and other tools. No team size is given for this founding role.

Waymo★3.0 (61)· London

You will use Python, deep learning frameworks (JAX, TensorFlow/PyTorch), and C++ (preferred) to develop data-selection algorithms and scaling laws for foundation model training. The AI Foundations team builds machine learning solutions for autonomous driving, focusing on reinforcement learning, generative modeling, and robust evaluation to improve the Waymo Driver. You will report to a Senior Staff Software Engineer.

Google★4.3 (6.2k)· London

Manage engineers building Google’s Learning Platforms within the Global Business Organization, which powers Google’s ecosystem of products and services for customers and partners. Work with back-end languages (Java, Python, Golang, C++) and front-end (JavaScript, TypeScript, HTML, CSS), plus ML model fine-tuning and evaluation.

This role develops generative AI applications using Java, Python, React or Angular, LangChain, LlamaIndex, Hugging Face, Docker, Kubernetes, and AWS, with tools like GitHub Copilot. You will build scalable, AI-powered solutions for Citi’s global finance operations.

Work with Nvidia GB200 72NVL CX8 and AMD MIxxx architectures, coding in C, C++, C#, Java, JavaScript, or Python to benchmark, profile, and debug GPU clusters. You will help build foundational models powering Microsoft’s personalized AI assistant, Copilot, spanning training and inference infrastructure, model architecture, and data curation.

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.

White & Case★4.0 (120)· London

Works with Python, JavaScript, MCP, agentic AI frameworks, LLMs, and cloud platforms (Azure, AWS) to architect and deploy AI tools. As technical lead of the Applied AI Lab, the role oversees design, development, testing, and deployment of AI solutions to support legal practice and firm-wide innovation. Manages and develops a multidisciplinary team of legal engineers.

You will work with Python (NumPy, SciPy), C++, large datasets, distributed systems, and high-performance computing concepts. The team builds high-performance trading and analytics platforms for a HFT leader that transforms sports data into competitive insight, and you will convert prototype models into production systems and optimize for low latency and scalability.

You will work with Python, JavaScript, Model Context Protocol (MCP), agentic AI frameworks, LLMs, and cloud platforms (Azure, AWS). As technical

Build high-performance trading and analytics platforms using Python (NumPy, SciPy) and optionally C++, with large datasets, numerical computing, distributed systems, and high-performance computing. The team turns complex sports data into actionable insight for a HFT leader.

Work with Python, PyTorch, scipy, scikit-learn, numpy, pandas, MLflow, Docker, Kubernetes, Ray, and GCP to build and scale distributed compute for research workloads. Phaidra creates AI-powered control systems for the industrial sector using reinforcement learning to enable facilities to learn and improve automatically.

Work with modern C++, Python, and C# in a Linux environment using Git. You will design and maintain high-performance pricing libraries, risk engines, and real-time trading applications for equity derivatives in a front-office quantitative technology team.

At Axon Labs you will own production infrastructure across multi-region cloud and latency-sensitive environments using AWS, Python, C++, Kubernetes, Terraform, CI/CD, PostgreSQL, TimescaleDB, Kafka, Redis, low-latency messaging, Grafana, Prometheus, and Loki. The company is a systematic trading and research lab that builds decision engines running in live markets, with multiple strategies already in production across venues.

Citi★3.9 (21k)· London

Build and scale AI-powered financial systems using Java, Spring, React/Angular, Python, FastAPI, Docker, and GitHub Copilot within Citi’s global tech environment. You will design generative AI agents, LLM workflows, and RAG pipelines while working on enterprise microservices, mobile, or front-end development. This role is for an individual contributor on an agile team.

Build and operate a Kubernetes-native cloud platform for GPU inference workloads, using Python or Go. You'll lead technical designs, own areas like request routing and adaptive scheduling, and implement optimizations such as speculative decoding and KV-cache reuse, working with Prometheus, Grafana, and OpenTelemetry.

Deloitte★3.9 (14k)· London

You will work with Python, JavaScript, Kafka, Azure, Kubernetes, Terraform, Helm, LangChain, PySpark, Databricks, and ADLS. You will design, develop, and deploy production-grade GenAI and machine learning systems for the GenAI team within Deloitte’s Data & AI organisation.

You will develop large language models, reinforcement learning, generative AI, and optimization techniques using Python, PyTorch, TensorFlow, or JAX, with exposure to CUDA and distributed training. The team applies advanced machine learning research to real-world semiconductor design and AI systems.

You will work with LLMs, generative AI, Python, JavaScript, React, HTML, CSS, Microsoft Azure, and DevOps tools (CI/CD, Git). You will design, build, and deploy AI applications that enhance productivity, automate workflows, and support business decision-making across a growing technology function.

Checkout.com★3.8 (15)· London

You will work with LLMs (GPT, BERT, Llama, Gemini), Python/JavaScript, AI frameworks (LangChain, PydanticAI), cloud platforms (AWS/GCP/Azure), Docker, Kubernetes, and Terraform. As part of Checkout.com’s AI Centre of Excellence, you will design, build, and deploy Generative AI solutions (chatbots, assistants, knowledge extraction tools) to enhance products and streamline business processes.

Jump Trading★3.8 (11)· London

You will work with C/C++, Python, CUDA, and other low-level GPU languages, plus deep learning libraries like PyTorch, JAX, or TensorFlow, to build and optimize large-scale ML systems. You will collaborate with researchers and traders to develop frameworks for financial ML, optimize training pipelines on HPC clusters, and integrate models into low-latency production systems.

Jump Trading★3.8 (11)· London

You'll work with C++/Python/CUDA, PyTorch/JAX/TensorFlow, and HPC clusters to build state-of-the-art ML systems for quantitative finance. You'll collaborate with researchers and quants to develop flexible frameworks, optimize training pipelines, and integrate low-latency inference into production systems.

Graphcore★3.0 (4)· London

Develop and optimise AI models using PyTorch or JAX, scaling them to thousands of accelerators. As part of Graphcore’s Applied AI team, you will build reference applications and optimise kernels for the company’s specialised AI hardware. You will collaborate with software development and research teams to advance the technology.

You will work with Python, PyTorch, and geometric deep learning methods (e.g., NeRF, SLAM, VIO, feature matching) to build scene matching, geo-registration, and 3D reconstruction systems for defence AI. The team specialises in scene understanding and localisation, delivering AI capabilities for machine perception and human decision-making under real-world hardware and adversarial constraints.