5 of 5 Permanent Semantic Search Jobs in the UK

Python, PyTorch, TensorFlow, JAX NLP, deep learning, model optimisation Evaluation frameworks and guardrails Data & Platforms Vector databases (Pinecone, Weaviate, FAISS, Milvus) Knowledge graphs and semantic search Data engineering pipelines MLOps & Deployment CI/CD for ML, model monitoring, versioning Kubernetes, Docker, serverless architectures MLflow, Kubeflow, SageMaker or similar … Architecture Azure AI, AWS AI/Bedrock, Google Vertex AI API-led architectures and microservices Security, governance, and responsible AI Frameworks & Tooling LangChain, LlamaIndex, Semantic Kernel or equivalent Integration with enterprise systems (CRM, ERP, collaboration platforms) Desirable Experience in regulated environments AI ethics, governance, and compliance knowledge Background ...

Haystack, AutoGen, and OpenAI Assistant/Responses API patterns. Design and implement high-performance Retrieval-Augmented Generation (RAG) pipelines, including: Hybrid (keyword + vector) search Reranking and embedding optimization Chunking and document preprocessing strategies Evaluation and regression testing harnesses Develop APIs, microservices, and serverless GenAI workflows for scalable, secure … modern GenAI ecosystem. Deep understanding of LLM behavior, prompt optimization, embeddings, retrieval strategies, and data preparation workflows. Practical experience with vector databases and semantic search systems. Comfortable working in Linux environments with Bash/PowerShell, containers, and cloud infrastructure. Strong communication skills, creativity, and a systems-thinking mindset. ...

distillation of LLMs (e.g., GPT, Llama, Claude, Gemini), machine learning libraries (e.g. scikit-learn, XGBoost). Experience with data storage for AI, vector databases, semantic search, and knowledge graphs. Contributions to open-source AI projects or research publications. Familiarity with AI security, privacy, and compliance standards e.g. ISO42001. ...

design and build backend systems that are performant, reliable, and maintainable. Database Expertise: Strong experience with PostgreSQL and familiarity with vector databases for semantic search and retrieval. Strong Problem-Solving Skills: Ability to debug complex systems, optimize for latency and cost, and navigate ambiguity. Proven Track Record: Demonstrable ...

optimise RAG (Retrieval Augmented Generation) pipelines Develop AI agents with tool integration and multi-step workflows Engineer scalable Python-based services and APIs Implement semantic search using vector databases Deploy and manage AI solutions within cloud environments (Azure preferred) Contribute to best practices across evaluation, monitoring and reliability ...