1 to 25 of 379 LangChain Jobs in London

production environments. Proficiency in Python 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 containerization (Docker, Kubernetes). Experience More ❯

production environments. Proficiency in Python 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 containerization (Docker, Kubernetes). Experience More ❯

grade applications Generative AI: Demonstratable 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. AI/ML: Hands on experience with training and evaluating BERT-like models in real-world applications, especially in NLP or classification problems Data More ❯

. Understanding of advanced machine 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. #J-18808-Ljbffr More ❯

/ML Generative AI: Demonstratable 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 (like GPT4 Omni, Qwen-vl More ❯

Python. Experience with cloud platforms like Google Cloud Platform (GCP), Amazon Web Services (AWS), or Microsoft Azure. Good knowledge and experience with generative AI concepts, frameworks and models (e.g., Langchain, OpenAI). Good knowledge and experience with machine learning concepts and frameworks (e.g., TensorFlow, PyTorch). Strong problem-solving and analytical skills. Excellent communication and collaboration skills. Ability to work … Have experience interacting with generative models via API endpoints. Are familiar with concepts of AI application development (e.g., RAG models, fine-tuning). Are familiar with AI frameworks (e.g., Langchain). #J-18808-Ljbffr More ❯

of-the-art algorithms and pipelines for efficient data processing, feature engineering, and data transformation tailored for LLM and GenAI applications. GenAI Application Development: Apply and integrate frameworks like LangChain and Hugging Face Transformers to build modular, scalable, and robust Generative AI data pipelines and applications. Prompt Engineering Application: Apply advanced prompt engineering techniques to optimize LLM performance for specific … or a related field. Programming and Frameworks: Hands-on experience with Python, TensorFlow or PyTorch, and NLP libraries such as spaCy and Hugging Face. GenAI Tools: Practical experience with LangChain, Hugging Face Transformers, and embedding models for building GenAI applications. Prompt Engineering: Expertise in prompt engineering, including prompt tuning, chaining, and optimization techniques. LLM Evaluation: Experience evaluating LLM outputs, including More ❯

Qualifications Skills & Expertise Strong experience in machine learning, deep learning, and statistical analysis. Expertise in Python, with proficiency in ML and NLP libraries such as Scikit-learn, TensorFlow, Faiss, LangChain, Transformers and PyTorch. Experience with big data tools such as Hadoop, Spark, and Hive. Familiarity with CI/CD and MLOps frameworks for building end-to-end ML pipelines. Proven More ❯

You will be part of a hands-on, globally distributed group tackling novel R & D problems that directly impact customers. OUR TECHNOLOGY STACK: Python • Agentic tools (Autogen, Semantic Kernel, LangChain) • SQL • MongoDB • Third-party LLM APIs • LiteLLM • MLflow • Google Cloud Platform • Docker • PyTorch • Hugging Face Transformers • SPARQL • Kubernetes WHAT YOU WILL BE DOING AT BEAMERY Join us at the forefront More ❯

and analyzing large heterogeneous data sets related to drug discovery. -LLM Experience: Experience with LLMs (fine-tuning, pretraining, continued pretraining, inference, RAG, and building multi-agent workflows using Llamaindex, Langchain, LangGraph, vector databases, etc.). -Production-Grade Models: Significant expertise in building production-grade machine learning models in industry and/or academic research settings, building, training, and deploying ML. More ❯

Bonus Points If I Have 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 exciting journey of growth and More ❯

production-grade AI capabilities. Responsibilities Design and implement secure, cloud-native microservices and APIs using Python for data and AI services. Architect LLM-integrated systems (e.g., RAG pipelines) leveraging LangChain, vector databases, and GenAI providers (e.g., AWS Bedrock, OpenAI). Automate infrastructure and CI/CD workflows using Docker, Kubernetes, Helm, and Terraform across AWS and/or Azure. Develop … cloud-native architecture (AWS or Azure). Hands-on with tools such as Kafka, Spark, Airflow, Redis, Elasticsearch, and container orchestration (K8s). Experience with GenAI tools such as LangChain, RAG systems, Bedrock/OpenAI APIs Solid grasp of CI/CD, IAC (Terraform, Helm), and monitoring (Prometheus, Grafana) Experience deploying in cloud environments with EC2, Lambda, S3, RDS, EKS More ❯

engineering, MLOps and/or backend/infra-focused roles Experience integrating LLMs into enterprise SaaS or internal tooling Strong Python experience with ML/LLM libraries (e.g., Transformers, LangChain, LangGraph, OpenAI APIs) Experience with cloud platforms (AWS, GCP, or Azure), deployment, and CI/CD pipelines Familiarity with containerization (Docker, Kubernetes) and observability (e.g., Prometheus, Grafana) A builder mindset More ❯

engineering, MLOps and/or backend/infra-focused roles Experience integrating LLMs into enterprise SaaS or internal tooling Strong Python experience with ML/LLM libraries (e.g., Transformers, LangChain, LangGraph, OpenAI APIs) Experience with cloud platforms (AWS, GCP, or Azure), deployment, and CI/CD pipelines Familiarity with containerization (Docker, Kubernetes) and observability (e.g., Prometheus, Grafana) A builder mindset More ❯

understanding of backend performance optimization and debugging. Knowledge of AWS SageMaker and data analytics tools. Proficiency in frameworks TensorFlow, PyTorch, or similar. Preferred Qualifications, Capabilities, and Skills: Familiarity with LangChain, Langgraph, or any Agentic Frameworks is a strong plus. Python engineering experience React About Us J.P. Morgan is a global leader in financial services, providing strategic advice and products to More ❯

NumPy, or Spark. At least 2 years' experience with machine learning, deep learning, or AI systems. Familiarity with key libraries and frameworks such as TensorFlow, Scikit-learn, PyTorch, Transformers, LangChain, BeautifulSoup, and OpenCV. Experience with AI APIs and platforms (e.g., OpenAI, Bedrock, Gemini, Anthropic). Knowledge of cloud infrastructure (ideally AWS), Kubernetes, and relevant SDKs (e.g., boto3, confluent-kafka). More ❯

NumPy, or Spark. At least 2 years' experience with machine learning, deep learning, or AI systems. Familiarity with key libraries and frameworks such as TensorFlow, Scikit-learn, PyTorch, Transformers, LangChain, BeautifulSoup, and OpenCV. Experience with AI APIs and platforms (e.g., OpenAI, Bedrock, Gemini, Anthropic). Knowledge of cloud infrastructure (ideally AWS), Kubernetes, and relevant SDKs (e.g., boto3, confluent-kafka). More ❯

NumPy, or Spark. At least 2 years' experience with machine learning, deep learning, or AI systems. Familiarity with key libraries and frameworks such as TensorFlow, Scikit-learn, PyTorch, Transformers, LangChain, BeautifulSoup, and OpenCV. Experience with AI APIs and platforms (e.g., OpenAI, Bedrock, Gemini, Anthropic). Knowledge of cloud infrastructure (ideally AWS), Kubernetes, and relevant SDKs (e.g., boto3, confluent-kafka). More ❯

NumPy, or Spark. At least 2 years' experience with machine learning, deep learning, or AI systems. Familiarity with key libraries and frameworks such as TensorFlow, Scikit-learn, PyTorch, Transformers, LangChain, BeautifulSoup, and OpenCV. Experience with AI APIs and platforms (e.g., OpenAI, Bedrock, Gemini, Anthropic). Knowledge of cloud infrastructure (ideally AWS), Kubernetes, and relevant SDKs (e.g., boto3, confluent-kafka). More ❯

ReAct for building more effective 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 Preferably hands-on experience with More ❯

Science, AI, Computer Science, or related quantitative field Experience: 5+ years in data science roles with platform/product experience 2+ years working on RAG implementations using tools like LangChain, LlamaIndex, or custom vector stores Experience building or deploying Agentic AI architectures (e.g., AutoGPT, CrewAI, OpenAgents) Strong grasp of CRM systems and finance/savings data (transaction flows, compliance, user More ❯

including test-driven development (TDD), Behaviour-driven development (BDD), integration testing and performance testing Some experience with AI tools (one of more of) Python, LLM(Large Language models), RAG, Langchain Set Yourself apart with: Bachelor's/Master's degree in Computer Science or related field Experienceof working on large scale, complex, and distributed applications in an Agile environment Experience More ❯

NumPy, or Spark. At least 2 years' experience with machine learning, deep learning, or AI systems. Familiarity with key libraries and frameworks such as TensorFlow, Scikit-learn, PyTorch, Transformers, LangChain, BeautifulSoup, and OpenCV. Experience with AI APIs and platforms (e.g., OpenAI, Bedrock, Gemini, Anthropic). Knowledge of cloud infrastructure (ideally AWS), Kubernetes, and relevant SDKs (e.g., boto3, confluent-kafka). More ❯

and analyzing large heterogeneous data sets related to drug discovery. LLM Experience: Experience with LLMs (fine-tuning, pretraining, continued pretraining, inference, RAG, and building multi-agent workflows using Llamaindex, Langchain, LangGraph, vector databases, etc.). Production-Grade Models: Significant expertise in building production-grade machine learning models in industry and/or academic research settings, building, training, and deploying ML. More ❯

Have a broad understanding of data extraction, data manipulation and feature engineering techniques Are familiar with statistical methodologies. Have good communication skills Nice to have Experience with LangGraph or LangChain Experience with transport industry and/or geographical information systems (GIS) Experience with cloud infrastructure Experience with graph technology and/or algorithms Our technology stack Python and associated ML …/DS libraries (Scikit-learn, Numpy, LightlGBM, Pandas, LangChain/LangGraph, TensorFlow, etc ) PySpark AWS cloud infrastructure: EMR, ECS, Athena, etc. MLOps: Terraform, Docker, Airflow, MLFlow More information: Enjoy fantastic perks like private healthcare & dental insurance, a generous work from abroad policy, 2-for-1 share purchase plans, extra festive time off, and excellent family-friendly benefits. We prioritise career More ❯