1 to 25 of 26 Permanent Retrieval-Augmented Generation Jobs in Surrey

Level: Junior–Mid Overview: As a Developer Advocate focused on AI/GenAI, you will empower AI builders with practical LLM/RAG samples, vector search demos, and hands-on tutorials. You'll foster engagement and growth in the AI developer community while ensuring GitHub advocacy repositories remain organized, discoverable … date. Key Responsibilities: Build AI/GenAI sample applications, including prompt pipelines, embeddings, retrieval-augmented generation (RAG), and evaluation/reference implementations. Maintain GitHub repositories and automation for AI assets; standardize repo structure, documentation, and contribution models. Produce step-by-step tutorials, quickstarts ...

Level: Junior–Mid Overview: As a Developer Advocate focused on AI/GenAI, you will empower AI builders with practical LLM/RAG samples, vector search demos, and hands-on tutorials. You'll foster engagement and growth in the AI developer community while ensuring GitHub advocacy repositories remain organized, discoverable … date. Key Responsibilities: Build AI/GenAI sample applications, including prompt pipelines, embeddings, retrieval-augmented generation (RAG), and evaluation/reference implementations. Maintain GitHub repositories and automation for AI assets; standardize repo structure, documentation, and contribution models. Produce step-by-step tutorials, quickstarts ...

build and evolve Generative AI (GenAI) proof-of-concepts (POCs) for clients using techniques like Retrieval-Augmented Generation (RAG) and intelligent agents. Support the transition of these POCs into scalable, production-ready solutions. Contribute to the design and development of full-stack applications ...

build and evolve Generative AI (GenAI) proof-of-concepts (POCs) for clients using techniques like Retrieval-Augmented Generation (RAG) and intelligent agents. Support the transition of these POCs into scalable, production-ready solutions. Contribute to the design and development of full-stack applications ...

based systems (e.g. LangChain, LlamaIndex, AutoGen, custom agent frameworks) Familiarity with prompt engineering, tool calling, retrieval-augmented generation (RAG), and multi-agent workflows Experience integrating AI into real systems, APIs, event-driven architectures, data pipelines, and automation platforms (e.g. UiPath, Blue Prism) Comfortable experimenting ...

Responsibilities Design and implement AI/ML and Generative AI models for predictive analytics and marketing applications. Explore solutions using LLMs, embeddings, and RAG pipelines. Collaborate with data engineers on data quality, feature engineering, and pipeline optimization. Translate business needs into analytical solutions and communicate findings effectively. Requirements Bachelor ...

Responsibilities Design and implement AI/ML and Generative AI models for predictive analytics and marketing applications. Explore solutions using LLMs, embeddings, and RAG pipelines. Collaborate with data engineers on data quality, feature engineering, and pipeline optimization. Translate business needs into analytical solutions and communicate findings effectively. Requirements Bachelor ...

/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 ...

/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 ...

fine-tune LLM-based applications (chatbots, summarization, document Q&A, report generation, code assistants, etc.). Apply prompt engineering, RAG (Retrieval-Augmented Generation), and context-aware pipelines to ensure accuracy and relevance. Integrate AI models with enterprise systems, APIs, and data stores … ethics, security, and governance standards. Prepare and curate training datasets (structured/unstructured text, images, code). Apply data preprocessing, tokenization, and embedding generation techniques. Work with vector databases (Pinecone, Weaviate, FAISS, Chroma) for semantic retrieval use cases. Partner with business stakeholders to identify and shape ...

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 ...

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 ...

technical stakeholders GenAI work You will work with GenAI in ways that are grounded in real use cases and business value: Building RAG systems that improve search, content discovery or productivity rather than existing for their own sake Implementing guardrails so models do not leak PII or generate harmful … Experience with PyTorch or TensorFlow GenAI specific Hands on experience with LLM APIs or open source models such as Llama or Mistral Experience building RAG systems with vector databases such as FAISS, Pinecone or Weaviate Ability to evaluate and improve prompts and retrieval quality using clear metrics Understanding ...

technical stakeholders GenAI work You will work with GenAI in ways that are grounded in real use cases and business value: Building RAG systems that improve search, content discovery or productivity rather than existing for their own sake Implementing guardrails so models do not leak PII or generate harmful … Experience with PyTorch or TensorFlow GenAI specific Hands on experience with LLM APIs or open source models such as Llama or Mistral Experience building RAG systems with vector databases such as FAISS, Pinecone or Weaviate Ability to evaluate and improve prompts and retrieval quality using clear metrics Understanding ...

where users can query information directly through an integrated AI assistant. The Challenges You'll Work On Evaluating a retrieval-augmented-generation (RAG) system in production without labelled data Designing your own benchmarks from scratch Building an agentic retrieval pipeline that adapts ...

where users can query information directly through an integrated AI assistant. The Challenges You'll Work On Evaluating a retrieval-augmented-generation (RAG) system in production without labelled data Designing your own benchmarks from scratch Building an agentic retrieval pipeline that adapts ...

applicants but be currently resident and eligible to work in the UK Demonstrable experience of building and deploying complex AI applications using LLMs, RAG and agentic workflows GraphRAG/Knowledge Graph expertise - deep knowledge with Knowledge Graphs and vector databases Strong technical fluency - TypeScript/React, Langgraph/Langchain, neo4j ...

applicants but be currently resident and eligible to work in the UK Demonstrable experience of building and deploying complex AI applications using LLMs, RAG and agentic workflows GraphRAG/Knowledge Graph expertise - deep knowledge with Knowledge Graphs and vector databases Strong technical fluency - TypeScript/React, Langgraph/Langchain, neo4j ...

Transformer-based text classification (BERT/DistilBERT/RoBERTa) • Fine-tuning classification heads • Embeddings + cosine similarity search • Supporting LLM-adjacent work (not deep RAG) Tech Python, sklearn, XGBoost/LightGBM, HuggingFace Transformers, BERT-family models, embeddings, cloud-based ML, CI/CD awareness. What They're Looking For • Strong ...

Transformer-based text classification (BERT/DistilBERT/RoBERTa) • Fine-tuning classification heads • Embeddings + cosine similarity search • Supporting LLM-adjacent work (not deep RAG) Tech Python, sklearn, XGBoost/LightGBM, HuggingFace Transformers, BERT-family models, embeddings, cloud-based ML, CI/CD awareness. What They're Looking For • Strong ...

Developing and optimizing models for image recognition, object detection, and video analytics. NLP: Building sophisticated systems for sentiment analysis, entity extraction, semantic search, and RAG architectures leveraging LLMs. Generative AI: Exploring and implementing cutting-edge GenAI techniques for content creation, data augmentation, and innovative product features. SME Consulting & Mentorship … with Computer Vision tasks (e.g., CNNs, object detection models like YOLO). NLP: Expert practical experience in NLP techniques, including transformer models, embedding generation, and building complex text-based applications. 3. Leadership & Soft Skills Technical Leadership: Proven track record of leading complex data science projects from research ...

Developing and optimizing models for image recognition, object detection, and video analytics. NLP: Building sophisticated systems for sentiment analysis, entity extraction, semantic search, and RAG architectures leveraging LLMs. Generative AI: Exploring and implementing cutting-edge GenAI techniques for content creation, data augmentation, and innovative product features. SME Consulting & Mentorship … with Computer Vision tasks (e.g., CNNs, object detection models like YOLO). NLP: Expert practical experience in NLP techniques, including transformer models, embedding generation, and building complex text-based applications. 3. Leadership & Soft Skills Technical Leadership: Proven track record of leading complex data science projects from research ...

Have Skills: Strong background in application security, cloud security, or security architecture Hands-on experience with securing AI/ML systems, including LLMs, APIs, RAG pipelines, and vector stores Deep familiarity with AI security risks and threat modeling methodologies Working knowledge of modern DevSecOps practices and tools Excellent communication ...

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 ...

User-Defined Agent Logic: Creating a \"no-code\" engine where users can verbally define workflows and guardrails that the system executes deterministically. Hierarchical & Auditable RAG: Routing queries through complex layers of patient history, clinical guidelines, and organizational policies with full traceability. Resilient Orchestration: Managing long-running conversation states, tool usage … executor patterns and manage shared memory across agents. Prompt Engineering & Optimization: utilize programmatic approaches to compile and iteratively improve prompts based on evaluation metrics. RAG Optimization: Enhance retrieval signal through hybrid search, re-ranking, and query rewriting, ensuring high context precision and recall. Observability & Evals: Build robust tracing ...