You will work with Python, LLMs, agentic workflows, retrieval-augmented generation (RAG), and internal AI platforms. The Tactical AI Automations team deploys and supports AI tools across PIMCO's Portfolio Management and Analytics groups, including operational support for Lane Assist and POET (portfolio optimization tools).

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.

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'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.

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.

Work with Python, NumPy, pandas, SQL, dbt, Snowflake/Databricks, and LLMs to build and deploy ML models and agentic systems (function calling, multi-agent orchestration) for Planday’s scheduling and workforce management platform. You’ll ship production features on a small, high-impact team.

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.

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.

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.

Staff AI Engineer will use Python, Azure, LangChain, Semantic Kernel, LLMs, and RAG to build production-ready patterns for agentic AI, prompt engineering, and responsible AI. This cross-cutting role connects AI ambition to delivery across all Tech domains at Sainsbury's, creating reusable accelerators and standardising AI engineering division-wide.

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.

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.

Accenture★3.9 (29k)· London

You will work with Python, LangChain, LangGraph, AutoGen, FastAPI, REST APIs, vector databases, Git, CI/CD, and cloud platforms (Azure, GCP, or AWS) to build, deploy, and iterate on machine learning and generative AI solutions for clients across industries.

Accenture★3.9 (29k)· London

You will build production-grade agentic AI systems using LangGraph, CrewAI, AutoGen, OpenAI, Anthropic, Vertex AI, Kubernetes, Docker, Python, and Java. The role designs end-to-end multi-agent systems, RAG pipelines, and LLMOps (LangSmith, Braintrust) while embedding with client engineering teams to deliver enterprise solutions. No team size is stated.

Accenture★3.9 (29k)· London

You will design and deploy production-grade agentic AI systems using LangGraph, CrewAI, AutoGen, Python, OpenAI, Anthropic, Vertex AI, Kubernetes, Docker, Terraform, and LangSmith. The team builds multi-agent orchestrations, RAG pipelines, and LLMOps tooling for enterprise clients, embedding directly with client engineering teams to deliver scalable patterns.

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.

You will work with CUDA and Triton kernels, Python, Kubernetes, and AWS to build systems that train and serve large transformer and LLM models. The team creates and scales training pipelines and inference services for Fin’s AI Customer Agent, which resolves customer service queries across channels.

Wise★3.5 (42)· London

You'll build ML platform infrastructure using Python, Kotlin/Java, SQL, Airflow, Kubeflow, MLflow, and container-based deployment. Your team owns the model lifecycle platform for financial crime detection – designing training pipelines, model serving, evaluation, and monitoring systems from the ground up. This is a greenfield build with strong senior leadership investment.

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.

Version 1★3.9 (39)· London

Work with Python, LLMs, RAG systems, fine-tuning, embeddings, orchestration frameworks, and AI coding agents to design, prototype, and scale enterprise-grade AI products. Lead applied research across LLMs, agentic systems, retrieval architectures, and applied ML for Version 1, a technology and transformation solutions provider.