. 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. More ❯
Greater London, England, United Kingdom Hybrid / WFH Options
Intellect Group
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 ❯
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 ❯
Claude Code, Codex, and GitHub Copilot for technical analysis, code generation and code review. Hands-on experience with AI/ML frameworks (PyTorch, TensorFlow, HuggingFace) and LLM orchestration tools (LangChain, LangGraph, or similar) Experience deploying ML models using containerised solutions (Docker, Kubernetes) and frameworks like BentoML or equivalent. Familiarity with vector databases and retrieval pipelines for RAG architectures. Knowledge of More ❯
expertise in implementing RAG systems, designing prompt engineering frameworks, and developing multi-agent systems. You should be proficient with both commercial and open-source technologies, including popular frameworks like LangChain, Hugging Face, and PyTorch, as well as vector databases and embedding models. Your comprehensive understanding of the AI/ML ecosystem, including leading vendors, emerging startups, and key open-source 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 ❯
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 ❯
London, South East, England, United Kingdom Hybrid / WFH Options
Opus Recruitment Solutions Ltd
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 ❯
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 ❯
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 ❯
production environments, including ownership of key lifecycle stages: data collection, modeling, evaluation, deployment, and monitoring. • Proficiency in Python and modern ML and agentic frameworks such as PyTorch, TensorFlow, or LangChain, with experience packaging models into APIs or integrating them into applications. • A solid understanding of LLMs for natural language processing applications, including topics such as embeddings, prompt engineering and fine 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 ❯
learning techniques and GenAI concepts such as prompt engineering, chain-of-thought reasoning, prompt chaining, Retrieval-Augmented Generation (RAG), custom-built agents. Familiarity with LLM and agentic frameworks like LangChain, PydanticAI, or similar. Proficiency in ML-Ops practices and tools; strong understanding of DevOps and CI/CD. Experience with cloud platforms, e.g. AWS (preferred), GCP, and deploying models in 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 ❯
pipelines, and observability tools. Hands-on experience with languages and tools like Ruby, Java, React, GraphQL, AWS/GCP, and Kubernetes. Bonus: Experience with vector databases, LLM frameworks (e.g., LangChain, RAG), and open-source AI tools. Excellent communication, collaboration, and problem-solving skills. Strong organizational skills with a passion for continuous improvement. Agile Practices: Demonstrated success with agile product development More ❯
modular, distributed, and asynchronous systems Solid experience leading full-stack application development teams Expert-level proficiency in Python and hands-on experience with at least one LLM based framework (LangChain, LangGraph, LangSmith, LlamaIndex, Qdrant, etc ) Strong experience with asynchronous queues (e.g., Kafka, RabbitMQ) and asynchronous APIs Deep understanding of cloud infrastructure (AWS, GCP) and experience deploying and managing applications at More ❯
London, South East, England, United Kingdom Hybrid / WFH Options
XPERT-CAREER LTD
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 ❯
partners to match value proposition to business needs. Thrived as a another fast-paced SaaS startup or scale-up during a high-growth phase. Preferred to have: expertise with langchain and similar tools for multimodal AI projects. What's in it for you: £80-100k base salary with £25k additional commission Top 15% quartile equity options plan through an 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 ❯
on expertise in Python, SQL, ML frameworks (e.g. XGBoost, TensorFlow, PyTorch), and cloud tools (GCP, BigQuery, Vertex AI). Familiar with generative AI tools and frameworks (e.g. OpenAI, HuggingFace, LangChain). Deeply curious, commercially minded, and impact-driven with strong critical thinking skills. Comfortable in fast-paced environments with a proactive, self-starter mindset. Holds a relevant STEM degree (BSc More ❯
be nice if you have: Exposure to container orchestration (e.g., Kubernetes) Experience building or maintaining infrastructure for AI workloads, including support for agents, LLMs, or vector databases. Familiarity with LangChain, LangSmith, or similar agent orchestration and tracing tools. Experience managing and scaling applications in cloud environments, particularly with Azure. As part of our commitment to information security, all employees are More ❯
be nice if you have: Exposure to container orchestration (e.g., Kubernetes) Experience building or maintaining infrastructure for AI workloads, including support for agents, LLMs, or vector databases. Familiarity with LangChain, LangSmith, or similar agent orchestration and tracing tools. Experience managing and scaling applications in cloud environments, particularly with Azure. As part of our commitment to information security, all employees are 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 ❯
technical requirements and solution architecture for complex AI systems. Strong experience building and consuming API services in Python, using FastAPI or similar. Strong experience with LLM frameworks such as langchain, Pydantic-AI, Google ADK, OpenAI's Assistants, litellm, etc (it's not required to know them all), and an understanding of how they facilitate agentic AI development. Strong practical knowledge More ❯
