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

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.

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.

Circadia Health's ML Ops Engineer will work with Apache Airflow, AWS (Batch, EC2, S3, IAM, CloudWatch), MLflow, Docker, Python, Git, SQL, Snowflake, and edge devices. You own the ML infrastructure and pipelines for a clinical monitoring platform that identifies early signs of clinical deterioration using predictive models in cloud and edge environments.

You will work with Python, Kubernetes, LangChain, LangGraph, DSPy, LlamaIndex, OpenAI, and Anthropic to build and operate scalable services, APIs, and cloud-native infrastructure. You will design and deploy an enterprise AI platform for a leading investment firm, enabling secure consumption of Generative AI and autonomous systems across the business.

You will work with MongoDB, Postgres, Kinesis, Flink, Spark, ElasticSearch, Redis, Trino, Presto, Snowflake, Kubernetes, and public cloud. The Platform Engineering team designs and develops core data storage, streaming, caching, and indexing platforms that power Scale AI’s products for LLMs and generative models.

Lead a data ingestion team building the crawl, pipeline, and data-lake stack that supplies pre-training corpora for frontier models. You'll work with distributed compute (Ray, Beam, Spark), orchestration (Airflow, Prefect), storage formats (Parquet, JSONL, WARC), and object-store/lakehouse architectures. You will build and mentor a team of data ingestion engineers while staying hands-on across web crawling, extraction, and dataset delivery.

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 Terraform, Pulumi, OpenFGA, Authzed, Cedar, Topaz, OAuth 2.0, OIDC, SAML, JWT, EntraID, Okta, AWS, and frameworks like Java, Python, Node.js, .NET to design and implement identity infrastructure for authentication and authorization. You will support the Identity Engineering team, which builds core systems for Scale AI’s products that power advanced LLMs and generative models through RLHF, human data generation, and model evaluation.

Databricks★3.0 (21)· London

You will build GenAI applications using HuggingFace, LangChain, DSPy, pandas, scikit-learn, PyTorch, and deploy on AWS, Azure, or GCP. As part of Databricks’ AI FDE team, you deliver customer-facing engagements to productionize first-of-its-kind GenAI solutions, including RAG, multi-agent systems, and fine-tuning.

Zoopla★3.9 (18)· London

Work with Python, scikit-learn, PyTorch, TensorFlow, AWS (SageMaker, ECS, Lambda, SQS, DynamoDB), and MLOps tooling to build end-to-end ML pipelines. You will design and deploy production ML models that bring intelligent automation and predictive capability to the UK property market, using Alto's large dataset of real housing transactions.

Cint★3.5 (13)· London

Working with Large Language Models (LLMs), Python, SQL, and frameworks for LLM development, fine-tuning, and Prompt Engineering/RAG. You will build next-generation AI solutions that bridge traditional research data and synthetic intelligence, developing models for synthetic row generation, open-ended text generation, and data augmentation within Cint’s programmatic research marketplace.

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.

Databricks★3.0 (21)· London

You'll work with the Databricks Data Intelligence Platform, applying expertise in GenAI, LLMOps, MLOps, and tools like Apache Spark, HuggingFace, Langchain, and vector databases. As a Senior Specialist Solutions Engineer, you'll guide customers in architecting production-grade ML applications, lead technical sales engagements building MVMs and RAG implementations, and drive adoption through thought leadership and community engagement.

Build and maintain scalable backend data services using Python, FastAPI, SQL, Docker, Kubernetes, and CI/CD pipelines. You’ll work on the Signal Ocean platform—an AI-driven intelligence system for shipping and commodities—within the Modelling & Data Services team, collaborating with data science and product.

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.

Thomson Reuters★3.9 (4.3k)· London

You'll work with PyTorch, JAX, HuggingFace Transformers, vLLM, LLM APIs, Ray, Spark, and experiment tracking tools like Weights & Biases and MLflow on Thomson Reuters' Foundational Research division, which develops advanced algorithms and training techniques for Large Language Models including LLM training, post-training techniques for reasoning and workflows, data-centric ML, and evaluation. You'll design and implement scalable systems for training, fine-tuning, and evaluating LLMs while translating cutting-edge research into production implementations.

You'll build and operate large-scale data ingestion systems using Ray, Beam, Spark, or similar technologies—handling web crawling, extraction, normalization, and dataset delivery for Reflection's open-weight AI models. Working with pre-training and data quality teams, you'll design experiments to optimize crawling strategies and ingestion pipelines at multi-TB to PB scale, directly measuring impact on model performance. Reflection develops open foundational models and is hiring across a small, talent-dense team of researchers and engineers from DeepMind, OpenAI, Google Brain, and Anthropic.

Flo Health★4.8 (26)· London

You'll work with Python, MLflow, Databricks (Unity Catalog, Model Serving), AWS (EKS, Kubernetes, IAM), Terraform, and GitHub Actions to build Flo's GenAI platform—developing LLM evaluation judges, fine-tuning pipelines for health models (Llama, Gemma, MedGemma), and data infrastructure supporting 60+ production judges. Flo is the world's #1 women's health app with 80M+ monthly users, serving 7M paid subscribers with AI-powered, clinically-backed health features. You'll support an AI Platform team operating at scale across medical safety, model serving, and cross-functional partnerships with OpenAI, Google, Anthropic, and Databricks.