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.

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.

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

Cloudflare★3.2 (1.8k)· London

Interns work with Rust, C, Go, Python, and Gitlab/Github. Cloudflare’s Research Team solves difficult problems in security, privacy, and systems at scale. Projects may involve AI, distributed systems, privacy, and trusted execution environments.

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.

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.

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'll work with Python, Rust, ONNX, Chalk.ai, and GCP (Kubernetes, BigQuery, Agent Platform Endpoints). The team productionizes 10+ ML models for route assignment, delivery prediction, and

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.

Work with Python, SQL, and ML stacks (PyTorch, TRL) to build evaluation and data pipelines for LLMs and AI coding agents. The team owns how AI agents generate, analyze, and improve Kotlin code across Android, KMP, and server platforms, creating benchmarks and post-training pipelines.

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.

You will work with Python, TypeScript/JavaScript, Java, or C++ and cloud platforms (AWS, GCP, Azure) to build and deploy end-to-end generative and agentic AI applications, create training datasets, and design evaluation pipelines for LLMs. The Global Public Sector team builds custom AI applications for government clients, impacting millions of citizens.

You'll architect and deploy AI systems generating ad creatives using LLMs, vision and diffusion models, code generation, and multimodal asset generation, working with Python, JavaScript/TypeScript, and HTML. The Creative GenAI team at Liftoff—an AI-powered performance marketing platform serving 6,600+ mobile businesses—tackles end-to-end creative production including interactive playables, from prototyping through production pipelines. You'll report to the Senior Director of Creative GenAI, mentor engineers, and drive innovation in generative AI for ad tech.

You'll work with Rust, C++, or Go alongside Python, Linux/Windows systems, and virtualization technologies like cgroups, KVM, and gVisor. The Sandbox service team builds secure, scalable infrastructure that grants AI models safe, controlled access to computational environments for code execution, tool interaction, and reinforcement learning across xAI's training and product workloads.

You'll work primarily in Rust (or C++/Go) building xAI's API infrastructure that serves large language models to developers globally, handling billions of tokens per minute with low latency and high availability. Responsibilities span model serving, request routing, SDK development, rate limiting, observability, and scaling. You'll need expertise in distributed systems, databases like PostgreSQL and MongoDB, service reliability practices, and ideally experience with LLM inference engines like vLLM or TensorRT, plus Kubernetes and gRPC.

You'll develop and deploy reinforcement learning agents using Python, Rust, and modern C++ to build the autonomy brain for Helsing's CA-1 Europa unmanned combat aerial vehicle, integrating state-of-the-art RL techniques into real-time flight-ready systems. The role spans the full pipeline from large-scale simulation training through operational deployment, requiring deep expertise in model-free methods, multi-agent RL, and production AI integration with real-time latency constraints. Helsing is a defence AI company focused on autonomous systems for democratic nations.

You will develop computer vision models for object recognition, tracking, video understanding, and scene matching using deep learning architectures and state-of-the-art methods, optimizing them for hardware constraints and adversarial robustness. The role involves designing experiments, benchmarking performance in real-world scenarios, and collaborating across teams at Helsing, a defence AI company building AI-based capabilities for democratic protection. You should have an MSc in computer science, machine learning, or robotics with strong Python software engineering skills and experience deploying AI systems to production.

You'll develop cutting-edge AI safety techniques using Python, Rust, and modern C++ to evaluate uncertainty quantification, distribution shift detection, and adversarial robustness in Helsing's AI systems. The AI Assurance team designs evaluation frameworks and experimentation strategies for AI-based defense capabilities, working across research, engineering, and product teams to characterize failure modes and enhance operational safety in high-stakes sectors.

PostHog seeks an AI Research Engineer to develop deep learning models using PyTorch and Rust/CUDA/C, with strong transformer expertise and math background, for a new research team. You'll work on session replay analysis, user behavior prediction, and synthetic testing using petabytes of product analytics data to automatically surface insights and fixes for end users. This brand-new team offers substantial autonomy and direct customer influence, prioritizing shipped products over pure research.

Anthropic★5.0 (1)· London

You'll work with Python, PyTorch, JAX, and async frameworks like Trio to build reinforcement learning infrastructure and train agentic models at Anthropic, focusing on computer use, code generation, and reasoning capabilities for Claude. The role blends research and engineering, requiring you to architect distributed training systems, design novel RL environments, and optimize performance across GPU clusters while collaborating with alignment and applied teams.