1 to 25 of 172 LangChain Jobs

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 ❯

and evaluation of domain-specific LLMs , applying retrieval-augmented generation (RAG) and prompt engineering techniques. Contribute to the development of multi-agent systems using frameworks such as AutoGen , LangGraph , LangChain , or CrewAI . Support the integration of AI safety techniques into system design and deployment. Help implement real-time and batch inference pipelines with secure APIs (REST/gRPC, event More ❯

Language Models (fine tuning, RAG, agents) 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 More ❯

platform components from conception through production deployment Who You Are Expert proficiency in Python, JavaScript, and modern web frameworks Deep experience with AI/ML frameworks (PyTorch, TensorFlow, Transformers, LangChain) Mastery of prompt engineering and fine-tuning Large Language Models Proficient in vector databases (Pinecone, Weaviate, Milvus) and embedding technologies Expert in building RAG (Retrieval-Augmented Generation) systems at scale More ❯

platform components from conception through production deployment Who You Are Expert proficiency in Python, JavaScript, and modern web frameworks Deep experience with AI/ML frameworks (PyTorch, TensorFlow, Transformers, LangChain) Mastery of prompt engineering and fine-tuning Large Language Models Proficient in vector databases (Pinecone, Weaviate, Milvus) and embedding technologies Expert in building RAG (Retrieval-Augmented Generation) systems at scale More ❯

Statistical testing experience Experience with AWS Bedrock Experience with C# Containerization via Docker. Awareness of basic data science and generative AI methods. Exposure to generative AI application frameworks like LangChain, LlamaIndex, SmolAgents and griptape. What's in it for you? Join an ever-growing, market disrupting, global company where the teams - comprised of the best of the best - work in More ❯

in Python and SQL, and fluency with leading ML/AI frameworks (e.g., scikit-learn, TensorFlow, PyTorch) Direct experience with GenAI/LLM technologies, including tools like Hugging Face, LangChain, OpenAI APIs, vector databases, and fine-tuning methods Deep knowledge of machine learning algorithms (supervised, unsupervised, deep learning), including model evaluation, explainability, and selection for business-critical use cases Strong More ❯

services or insurance sectors advantageous. Familiarity with AzureML, Databricks, related Azure technologies, Docker, Kubernetes, and containerization is advantageous. Advanced proficiency in Python, and familiarity with AI frameworks such as LangChain Skilled in designing and operationalising AI Ops frameworks within cloud-based production environments. Exceptional communication skills, clearly articulating technical concepts to diverse stakeholders. Excellent organisational, time management, and prioritisation skills. More ❯

services or insurance sectors advantageous. Familiarity with AzureML, Databricks, related Azure technologies, Docker, Kubernetes, and containerization is advantageous. Advanced proficiency in Python, and familiarity with AI frameworks such as LangChain Skilled in designing and operationalising AI Ops frameworks within cloud-based production environments. Exceptional communication skills, clearly articulating technical concepts to diverse stakeholders. Excellent organisational, time management, and prioritisation skills. More ❯

control (Git) Experience working in cloud environments (AWS, GCP, or Azure) Ability to work independently and communicate effectively in a remote team Bonus Points Experience with Hugging Face Transformers , LangChain , or RAG pipelines Knowledge of MLOps tools (e.g., MLflow, Weights & Biases, Docker, Kubernetes) Exposure to data engineering or DevOps practices Contributions to open-source AI projects or research publications What More ❯

control (Git) Experience working in cloud environments (AWS, GCP, or Azure) Ability to work independently and communicate effectively in a remote team Bonus Points Experience with Hugging Face Transformers , LangChain , or RAG pipelines Knowledge of MLOps tools (e.g. MLflow, Weights & Biases, Docker, Kubernetes) Exposure to data engineering or DevOps practices Contributions to open-source AI projects or research publications What More ❯

pipelines for continuous model improvement Collaborate with cross-functional teams-research, product, and engineering-to embed AI capabilities into products and services Evaluate and select appropriate AI frameworks (e.g., LangChain, LlamaIndex) to integrate agent components seamlessly with enterprise systems Build full-stack applications (front-end interfaces and back-end APIs) using modern languages and frameworks (React/Angular, Python, Java More ❯

SQL The ability to build AI-driven solutions using large language models (LLMs), and techniques such as retrieval-augmented generation (RAG) and agent-based approaches, supported by frameworks like LangChain and CrewAI Skills in leveraging AI model APIs (e.g. OpenAI, Anthropic) and rapid prototyping tools such as Streamlit, along with AI-native developer tools like Cursor, to bring ideas to More ❯

priorities and influence the product 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 Experience building production-grade machine More ❯

software development Prior consulting experience essential Strong technical knowledge of GenAI and ML, including LLMs, RAG, MLOps, and prompt engineering Familiarity with platforms such as AWS Bedrock, Google Vertex, LangChain, or LlamaIndex Experience with both legacy systems and modern tech stacks Proven track record in agile delivery and digital transformation Excellent communication, analytical, and stakeholder management skills Willingness to travel More ❯

of Docker , CI/CD workflows, and automation pipelines Familiarity with MLOps tooling such as MLFlow, Git version control, and environment management Desirable Skills & Interests: Experience with frameworks like LangChain , Langflow , or similar tools for building AI agents Understanding of Large Language Models (LLMs) and intelligent automation workflows Experience building high-availability, scalable systems using microservices or event-driven architecture More ❯

e.g. databases, software engineering practices, cloud computing - especially AWS) and data science (e.g. machine learning process) Excellent knowledge of Python includingPytorch, Tensorflow andSKLearn as well as initial knowledge of LangChain andRAGAS. Familiarity with CI/CD workflows is required and experience with containerisation and deployment using Docker/Kubernetes will be considered a plus 1+ year experience working in relevant More ❯

/distillation of large-scale language models, with hands-on expertise in SFT, PPO, and reward modeling. Deep proficiency in Python and AI/ML frameworks such as PyTorch, LangChain, LangGraph, GraphRAG, and AutoGen. Experience with modern vector and graph databases (e.g., ChromaDB, Neo4j) and LLMOps platforms (e.g., Azure, Databricks, Azure OpenAI). Proven track record of delivering scalable AI More ❯

as SageMaker, Vertex AI or Azure Machine Learning Studio. Good knowledge of DevOps practices and tools (e.g.: Git, Docker, Kubernetes). Familiarity with AI platforms and frameworks such as LangChain, Llamaindex and, HugginFace. Expertise in data manipulation, data visualisation, and statistical modelling libraries (e.g.: pandas, NumPy, Matplotlib, scikit-learn). Skills in data visualisation tools (e.g.: Tableau, PowerBI). Excellent More ❯

governance. AI Infrastructure & MLOps: Experience with cloud AI services, model deployment, monitoring, and CI/CD pipelines for ML models (MLOps best practices). Example Tools & Technologies: Frameworks & Libraries: LangChain, Hugging Face Transformers, PyTorch, TensorFlow, Scikit-learn Agentic AI Tools: OpenAI GPT models, Crew,AI, Cohere, Pinecone (for vector databases), AutoGPT Data Engineering & ML Pipelines: Apache Airflow, MLflow, Kubeflow, dbt More ❯

skills (Grafana, Prometheus, ELK stack) Nice to Have Experience with GraphQL federation and Apollo Server. Knowledge of AI/ML APIs and LLM-based chatbot APIs (OpenAI, Hugging Face, LangChain). Experience with streaming technologies (Kafka, WebSockets, Golang-based streaming). Prior work with AI-powered data mapping, recommender systems, and real-time processing APIs. Physical Demands Physical demands include More ❯

systems. Excellent analytical and problem-solving skills. Effective communication of complex ideas. Ability to work independently and collaboratively. Preferred Skills: Experience building scalable applications with LLMs using frameworks like LangChain, LlamaIndex, Hugging Face, etc. Deep knowledge of RAG implementation and enhancements. Benefits & perks (UK full-time employees): Generous PTO and holidays. Comprehensive medical and dental insurance. Paid parental leave More ❯

Docker, Kubernetes, NVIDIA Triton), and backend development (REST API, OpenAPI, Swagger) • Language: Fluent in written and spoken English • Nice-to-have: Experience in LLM frameworks such as Haystack/LangChain, PyTorch, and proficiency in written and spoken German Responsibilities: • Design and implement software solutions in Python and C# in the field of artificial intelligence and machine learning • Conceptualize and test More ❯

pre-trained open source models Strong understanding of machine learning workflows, including model evaluations and LLM fine-tuning Familiarity with AI orchestration and agent-based systems and best practices (LangChain, AutoGen, n8n) Excellent problem-solving skills and the ability to work independently and collaboratively. Strong communication skills and the ability to translate technical concepts to non-technical stakeholders The person More ❯

Have good communication skills. Nice to have Experience deploying LLMs and agent-based systems Our technology stack Python and associated ML/DS libraries (scikit-learn, numpy, pandas, LightGBM, LangChain/LangGraph, TensorFlow, etc ) PySpark AWS cloud infrastructure: EMR, ECS, ECR, Athena, etc. MLOps: Terraform, Docker, Spacelift, Airflow, MLFlow Monitoring: New Relic CI/CD: Jenkins, Github Actions More information More ❯