10 of 10 Permanent Faiss Jobs in England

orchestration AI/ML Engineering 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 ...

OpenAI, Anthropic, Google Gemini, and Mistral, including deployment through Azure OpenAI Service or Vertex AI. Implement RAG architectures and manage vector databases (Pinecone, Weaviate, FAISS, Milvus) to power enterprise knowledge intelligence platforms. Data Platform & Engineering Excellence Lead the evolution of the enterprise data landscape using modern platforms such as Databricks ...

LLMOps pipelines, and AI observability. Experience in Enterprise-grade RAG-based solutions with LLMs (OpenAI, Hugging Face, LLaMA, etc.) and vector databases (Pinecone, Weaviate, FAISS, etc.). Ability to design enterprise-level AI/Gen AI platform/solutions with the client's existing enterprise stack. Hands-on mastery ...

ready AI systems. Experience in designing and implementing enterprise-grade AI solutions, including RAG-based solutions with LLMs and vector databases (e.g., Pinecone, Weaviate, FAISS). Proven experience in full stack development and AI/ML system implementation within enterprise environments. Strong grasp of advanced techniques such as complex task ...

such as Azure ML, AWS SageMaker, Vertex AI, Databricks, Modal, and Fly.io. Deploy and manage vector databases and embedding stores, including Pinecone, Weaviate, Milvus, FAISS, ChromaDB, and pgVector. Implement LLMOps/PromptOps practices using tools such as: Weights & Biases, MLflow, LangSmith, LangFuse, PromptLayer, Humanloop, Helicone, Arize Phoenix Benchmark, evaluate ...

application integrations ; ensure scalability, security, and observability. Select and integrate LLMs (Azure OpenAI, Google, AWS) and design RAG pipelines with vector stores (e.g., Pinecone , FAISS , Azure Cognitive Search ) and prompt strategies; optimize for latency/cost/accuracy. Architect agentic AI components (multi-agent workflows, gateways, registries, protocol interoperability ...

/LLMOps and AI observability Hands-on experience building enterprise RAG solutions using LLMs (e.g. OpenAI, Llama, Mistral, Claude) and vector databases (Pinecone, Weaviate, FAISS, etc.) Practical experience with GenAI frameworks such as LangChain, LlamaIndex, and agentic frameworks like AutoGen, CrewAI, LangGraph Strong Python expertise with AI/ML frameworks ...

model monitoring practices Proven track record of delivering large-scale enterprise AI platforms Desirable Skills Experience working with vector databases such as Pinecone or FAISS Knowledge of AI governance frameworks, compliance standards, and security architecture Relevant certifications in Azure AI, AWS ML, or Kubernetes This opportunity is well suited ...

Strong knowledge of Python, MLOps, LLMOps, CI/CD, model monitoring Experience delivering enterprise AI solutions at scale Desirable Experience with vector databases (Pinecone, FAISS) AI governance, compliance and security architecture Azure AI/AWS ML/Kubernetes certifications This role suits a technically hands-on architect who has delivered ...

LLMs in production Strong Python development skills Hands-on experience with: Prompt engineering and evaluation Retrieval-Augmented Generation (RAG) Embeddings and vector databases (e.g. FAISS, Pinecone, Weaviate, Chroma) Experience building LLM-backed services using FastAPI/Flask or similar Strong understanding of trade-offs around accuracy, latency, cost and scalability ...