1 to 25 of 63 LangChain Jobs in the UK

and ML libraries such as PyTorch, Hugging Face Transformers , or TensorFlow. Experience with vector search tools (e.g., FAISS, Pinecone, Weaviate) and retrieval frameworks (e.g., LangChain, LlamaIndex). Hands-on experience with fine-tuning and distillation of large language models. Comfortable with cloud platforms (Azure preferred), CI/CD tools, and More ❯

learning techniques, including graph-based processing, computer vision, natural language processing, and simulation modeling. Experience with generative AI and LLMs, such as LLamaIndex and LangChain Understanding of MLOps or LLMOps. Familiarity with Agile methodologies, preferably Scrum We are actively seeking candidates for full-time, remote work within the UK. More ❯

experience of RAG, including chunking strategies, vectorising and indexing data, retrieval strategies and reranking, prompting strategies, function calling. Our current tech-stack is OpenAI, LangChain, Azure AI, Python, pg_vector, Sinequa. Experience of multi-agent systems (LangGraph, Autogen, CrewAI etc.) would be a plus, as would experience of multimodal LLMs More ❯

NLP roles, with recent focus on LLMs and/or GenAI. Strong proficiency in Python, deep learning frameworks (PyTorch or TensorFlow), and GenAI libraries (LangChain, LlamaIndex, Transformers). Hands-on experience with vector search, embedding models, and retrieval pipelines. Familiarity with prompt engineering, prompt tuning, and evaluation of generative model More ❯

NLP roles, with recent focus on LLMs and/or GenAI. Strong proficiency in Python, deep learning frameworks (PyTorch or TensorFlow), and GenAI libraries (LangChain, LlamaIndex, Transformers). Hands-on experience with vector search, embedding models, and retrieval pipelines. Familiarity with prompt engineering, prompt tuning, and evaluation of generative model More ❯

Experience with AI engineering tools and technologies for fine tuning and serving custom LLMs in production and with other Gen AI tools such as, Langchain, LlamaIndex Experience working with Knowledge graphs based on text data Scala experience iM Getting To Join a rapidly evolving, industry-leading SaaS company on an More ❯

designing and implementing API-driven architectures. Experience with vector databases, retrieval-augmented generation (RAG), and multimodal AI systems. Familiarity with AI orchestration tools (e.g., LangChain, LlamaIndex, Ray, Dask). Understanding of MLOps and CI/CD pipelines for AI/ML models. Knowledge of security best practices for AI applications. More ❯

autonomous agents for complex property management workflows and decision-making processes Hands-on experience with AI/ML frameworks (TensorFlow, PyTorch), LLM orchestration tools (LangChain, LangGraph), MLOps practices and tooling (such as MLflow, Kubeflow, or similar), vector databases, and cloud platforms (AWS, Azure, GCP) with their AI/ML offerings More ❯

search concepts, such as indexing, scoring, relevancy, faceting, and query rewriting and expansion. Experience with semantic search frameworks and tools/databases such as LangChain, Faiss, and Pinecone. Understanding of nearest neighbor search concepts. About the Job: As a Generative AI Field Solutions Architect, you will support Google Cloud Sales More ❯

data pipelines, analytics tooling, or large-scale data processing. Interest in cloud-native and serverless architectures. Familiarity with tools such as TensorFlow, PyTorch, or LangChain is a plus. More ❯

ML development using frameworks like TensorFlow, PyTorch, and Scikit-learn. LLM Orchestration and Development Expertise in building LLM-powered applications using frameworks such as LangChain and LangGraph, including prompt engineering, fine-tuning, and workflow orchestration. Skilled in integrating LLMs with structured data systems (e.g., SQL databases, BigQuery) to enable natural More ❯

roadmap. What we look for: Experience building Generative AI applications, including RAG, agents, text2sql, fine-tuning, and deploying LLMs, with tools such as HuggingFace, Langchain, and OpenAI. Extensive hands-on industry data science experience, leveraging typical machine learning and data science tools including pandas, scikit-learn, and TensorFlow/PyTorch. More ❯

ML development using frameworks like TensorFlow, PyTorch, and Scikit-learn. LLM Orchestration and Development Expertise in building LLM-powered applications using frameworks such as LangChain and LangGraph, including prompt engineering, fine-tuning, and workflow orchestration. Skilled in integrating LLMs with structured data systems (e.g., SQL databases, BigQuery) to enable natural More ❯

communicate complex ideas and concepts effectively. Ability to work independently and collaboratively. Preferred Skills: Experience building scalable applications with LLMs, using frameworks such as LangChain, LlamaIndex, Hugging Face, etc. Depth of knowledge with RAG implementation and improvements. More ❯

. Familiarity with containerization (Docker) Understanding of RESTful APIs and microservices architecture. Experience with AI/ML-related tools and libraries (e.g., Hugging Face, LangChain, PyTorch) preferred A strong intuition for what makes products a joy to use. Empathy for how different users will need different things out of a More ❯

AI, with a focus on natural language processing and data analysis. Experience with generative models, large language models (LLMs), and entity resolution. Experience with LangChain or similar frameworks for building language model applications. Proficiency in Python and SQL, with strong skills in data manipulation and analysis. Expertise in AI frameworks More ❯

opportunity to participate in the upside of an ultra-growth venture. Have fun. Apply if: You have experience with our stack: Python, LlamaIndex/LangChain, PyTorch, HuggingFace, FastAPI, Postgres, SQLAlchemy, Alembic, OpenAI, Docker, Azure, Typescript, React. You have hands-on experience working with LLMs, RAG architectures, NLP, or applying Machine More ❯

with traditional ML models and feature engineering. Experience with LLMs. Strong programming skills (e.g., Python) and experience with modern ML frameworks (e.g., PyTorch, TensorFlow, LangChain). Collaborating with other Researchers, Product, Engineering and Business Stakeholders in an agile manner to demonstrate value and iterate with customer feedback. For immediate consideration More ❯

and implementing machine learning models using Python frameworks such as TensorFlow or PyTorch Practical knowledge of generative AI tooling including Hugging Face transformers and LangChain orchestration Specialisation in natural language processing and large language models, covering training methodologies, deployment strategies and optimisation techniques Familiarity with containerisation and orchestration technologies including More ❯

field such as Data Analytics, Computer Science, Machine Learning/AI, Mathematics, Physics, or Statistics. Expertise in fine-tuning large language models , vector databases , LangChain , LangGraph, Autogen, and prompt engineering . Proficiency in Python and SQL, with the ability to write production-quality code deployable on cloud platforms. Demonstrated experience More ❯

stack development experience with AI technologies/tools and apply it to user experiences or backend solutions. Experience with AI technologies like SageMaker, Vert.x, LangChain, Large Language Models, Prompt Engineering, DialogFlow, Python. Experience with at least one of the following: Front-end technologies like React, Angular, SwiftUI (iOS), Kotlin (Android More ❯

using generative AI tools and foundational models, including prototypes and production-ready solutions. Proficiency with modern LLM/AI tools (e.g., LlamaIndex, Amazon Q, LangChain, and vector databases), and a strong interest in exploring new tools and techniques within the GenAI ecosystem. Experience with AWS AI/ML services such More ❯

Biases. A solid background in software engineering and DevOps practices, MLOps deployment, and infrastructure. A knack for generative AI frameworks and SDKs, like RAG, Langchain/LangGraph, Semantic Kernel, and tools such as MS tooling, Co-Pilot Studio, ML Studio, Prompt flow, Kedro, etc. Proficiency with pipeline orchestration tools, such More ❯

low-latency decision-making. Enhance agent decision-making abilities through RL, planning, and heuristic algorithms. Design and implement multi-agent architectures using frameworks like LangChain, AutoGPT, CrewAI, or similar. Integrate AI agents with APIs, databases, and messaging systems (Kafka, RabbitMQ, MQTT). Monitor and optimize agent performance using observability tools More ❯

into AI assistants to optimal results and impact. Proven ROI of prior generative AI products and applications is a must. Proficiency in frameworks including LangChain for AI applications. Programming skills in Python, with experience in AI-driven automation and API integration. Experience working directly with customers, business stakeholders, and domain More ❯