Work with Python, SQL, JavaScript/TypeScript, NumPy, Pandas/Polars, visualization libraries, and deep learning frameworks (PyTorch, JAX, or TensorFlow) to design and deploy full-stack data-driven applications and machine learning solutions. You will be embedded with Arsenal's Men’s First Team Analysis department, building tools that directly support coaching and analysis workflows.

Tesco★3.5 (25k)· London

You will work with Java, Spring Boot, Kafka, Apache Flink, Apache Beam, NoSQL databases, Redis, and Apache Camel. The Tesco Personalisation team builds real-time, low-latency services for recommendations, offers, and experimentation across web, mobile, and in-store channels using streaming data and ML.

Lead a team of Data Scientists and ML Engineers building AI solutions for financial markets using LLMs, Generative AI, Deep Learning, Transformers, Agentic AI, Python, PyTorch, TensorFlow, Hugging Face, LangChain, Semantic Kernel, Azure AI Foundry, AWS AI Services, and MLOps/LLMOps practices.

Work with BigQuery, Airflow, BigTable, DynamoDB, Python, Scala, Spark, TensorFlow/PyTorch, Docker, Kubernetes, and LLMs building end-to-end ML pipelines. You'll own ML-powered features for the Recommendations Experience team, connecting 200M+ users with personalized music.

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.

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.

Work with Python, PyTorch (or JAX/TensorFlow), RL fine-tuning frameworks like TRL or verl, and distributed multi-GPU training. The Reinforcement Learning Team advances RL, Bayesian optimisation, AI agents, LLMs, and vision-language models, applying them to AI for science, chemistry, physics, and robotics while publishing at top venues.

You'll work with Python, TensorFlow, PyTorch, TFX, Kubeflow Pipelines, and model serving technologies like TensorFlow Serving and Triton on machine learning systems for personalization, recommendation engines, and ranking algorithms. At Fractal, a strategic AI partner to Fortune 500 companies, you'll design and train ML models, build data pipelines for large-scale datasets, deploy models to production, and lead A/B testing and experimentation across a multidisciplinary team.

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

AXIS Capital★5.0 (1)· London

You will work with Python, Azure AI services (Azure OpenAI, Azure AI Search), Git, LangChain, Semantic Kernel, and MLOps tools for model versioning, deployment, and monitoring. As deputy to the Head of Data Science & AI Delivery, you lead the day-to-day execution of AI delivery across strategic projects and use cases for AXIS Capital, a specialty insurance and reinsurance provider. You directly manage and contribute hands-on to technical design, code reviews, and solution delivery for a growing team of Data Scientists and AI Engineers.

You'll lead a 4–5 person team building machine learning systems using Python, TensorFlow, PyTorch, JAX, AWS, Docker, and Kubernetes for Super's Playstack platform, which powers sports betting and gaming experiences across Europe and Latin America. The role combines technical contribution, project management, and people leadership, focusing on predictive analytics, personalization, fraud detection, and real-time recommendations that enhance customer engagement in online gambling and sports betting.

DeepL★3.8 (4)· London

You will build and deploy state-of-the-art reinforcement learning pipelines at scale using Python, PyTorch, TensorFlow, or JAX, working with large compute clusters and ML infrastructure. As part of DeepL’s Foundation Model Task Adaptation team, you will post-train large (multi-modal) models to align them with human intent and enable capabilities like reasoning.

bp★3.8 (5.2k)· London

You will work with Python, Java, Azure, LLMs, vector DBs, and RAG patterns, using tools like LangChain, Haystack, and Hugging Face. As part of bp's AI organization, you will design and deploy scalable, production-grade AI applications such as conversational bots and AI-powered search for the oil and energy sector.

You will work with Python, Java, Azure, LLMs, vector DBs, RAG, and frameworks like LangChain, Haystack, Hugging Face, and Crew AI. The AI organization builds and deploys scalable, production-grade AI-powered applications for business value within the oil and energy/HR technology sector.

bp★3.8 (5.2k)· London

Design, develop and maintain production-grade AI applications using Python, Java, microservices, AWS/Azure/GCP, CI/CD, LLMs, vector DBs, RAG, and tools like LangChain, Haystack, Hugging Face, Weaviate, and LlamaIndex. The team builds scalable AI-powered applications—including conversational bots, AI search, unstructured data processing, and generative BI—to solve high-priority business problems.

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.

Fitch Ratings★3.8 (136)· London

You'll build ML/AI solutions using Python, FastAPI, PyTorch/TensorFlow, LangChain, LangGraph, and React/TypeScript within cloud-based microservices architectures. The agile team delivers software products for Fitch's BMI business, which provides data-driven market insights and risk analysis to customers globally. You'll design full-stack enterprise applications, implement GenAI features with LLM integration, and establish development best practices across the product suite.

FDM Group★2.9 (270)· London

The role involves Python, Java, microservices, CI/CD, cloud (AWS/Azure/GCP), LLMs, vector DBs, RAG, AI agents, and frameworks like LangChain, Haystack, Hugging Face, Weaviate, LlamaIndex, Crew AI, AutoGen. The team builds scalable AI-powered applications (conversational bots, AI search, unstructured data processing, GenBI) for a client in the energy sector.

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.

Research, design, and build production-grade ML models using Python, PyTorch, TensorFlow, or JAX, with deployment on cloud infrastructure (AWS, GCP, Azure) and on-device inference on clinical monitoring hardware. The work supports Circadia’s platform, which uses radar to capture contactless physiologic data paired with EHR-integrated clinical context, advancing novel areas like physiological foundation models and bed-exit detection. The role reports to a Principal ML Engineer.

Design, implement, and deploy machine learning models; develop and optimize LLM solutions; work with Python, TensorFlow, PyTorch. This intern will program and fine-tune AI tools for the IT teams at Medpace, a full-service clinical CRO that provides Phase I-IV drug development services.