9 of 9 Retrieval-Augmented Generation Jobs in Bedford

Proficiency in Python and familiarity with machine learning frameworks such as TensorFlow, PyTorch, and scikit-learn. Experience with Large Language Models, prompt engineering, and RAG implementations. Strong skills in data analytics, API development, and MLOps practices including CI/CD for ML. Excellent technical documentation and communication skills. Desirable knowledge ...

/Vertex AI, including fine-tuning, vector search, and low-latency inference. Build end-to-end LLM applications, leveraging RAG (Retrieval-Augmented Generation), agentic workflows, and prompt engineering. Implement robust evaluation frameworks to monitor LLM quality, hallucinations, token usage, and content safety. Develop … Looking For Essential 5+ years' experience in machine learning engineering or applied AI roles. Recent, demonstrable experience with LLMs, Generative AI, and/or RAG-based systems. Strong Python skills using frameworks such as PyTorch, TensorFlow, Hugging Face, or Google GenAI. Experience with vector databases and retrieval-based ...

Practical experience with AWS (and ideally Terraform, GitLab CI). Experience with agentic systems or LLM-powered automation (e.g. tool-augmented LLMs, RAG workflows, agents for complex workflows). If this sounds like you, reach ...

Server Actions) Proficiency in Supabase (database design, RLS, auth flows) Third-party API App Integration (incl. OpenAI, AI/LLM APIs) AI/ML: RAG implementation (Vector Databases, embeddings, semantic search) Stripe or Payment Gateway integration Solid Deployment Skills (e.g., Vercel, GCP) Experience with Git, Postman, and Webhooks for version ...

Important Client) profiles against property attributes to surface hyper-relevant travel recommendations. Intelligent Drafting: Build tools that assist managers in drafting complex itineraries, leveraging RAG to ensure every recommendation is backed by real-time perks and partnership data. System Orchestration: Design reliable, async environments for LLM tasks, ensuring source traceability ...

Journey and broader Azure AI-related questions. Designing and delivering custom AI solutions on Azure OpenAI Service and Microsoft Foundry, using patterns like RAG, function calling, tool/agent orchestration, and fine-tuning where appropriate. Implementing MCP-based integrations between AI services and existing application components (web apps, APIs, data … Design and optimize data pipelines that prepare structured and unstructured data for model training and RAG solutions. Implement vector search, embeddings, and retrieval-augmented generation workflows. Fine-tune or customize foundation models for domain-specific use cases. Create automated evaluation and monitoring systems ...

deployment. Deep knowledge of RAG Experience processing high volumens of documentation/text Strong knowledge of NLP and LLMs (transformers, fine-tuning, retrieval-augmented methods, agents). Experience conducting applied research and converting experimental outcomes into production systems. Familiarity with retraining workflows and performance monitoring. Understanding ...

this, you will work alongside the rest of the group to push the state-of-the-art and build the next generation of AI-native developer tools. The sky's the limit and you'll help us get there. Key Responsibilities Stay up to date with the state … apply it to the problem of Enterprise Vibe Coding; Make use of techniques such as In-Context Learning (Prompt Engineering & Retrieval Augmented Generation) and Tool Calling to guide Agents to perform as intended; Work in an "eval-driven development" methodology, applying evaluation techniques such ...

moving environment Immediate impact: Your code will run in production and support real users from day one. Technical depth: Multi-agent reasoning, voice-streaming, RAG optimisation and all in one system. Flexible setup: Remote across the EU, with optional co-working in London or Barcelona. What you'll do Obsessive … productionise multi-agent LLM systems that reason, plan, and coordinate. Develop FastAPI-based microservices optimised for low latency and high reliability. Engineer and evaluate RAG pipelines: hybrid retrieval, re-ranking, grounding, and context validation. Integrate real-time voice interfaces (STT/TTS, WebRTC, LiveKit) into intelligent conversational flows. ...