Central London, London, United Kingdom Hybrid / WFH Options
Staffworx Limited
custom LLM integrations). Exposure to AI ethics, data privacy, and compliance regulations. Prior experience in multi-agent systems or autonomous AI workflows. Hands-on experience with vector databases (Pinecone, Weaviate, FAISS) and AI embeddings. Remote WorkingSome remote working CountryUnited Kingdom LocationWC1 Job TypeContract or Permanent Start DateApr-Jul 25 Duration9 months initial or permanent Visa RequirementApplicants must be eligible More ❯
Nottingham, Nottinghamshire, United Kingdom Hybrid / WFH Options
NLP PEOPLE
tuning. Proficiency in Python, PyTorch, TensorFlow, and Hugging Face Transformers. Hands-on experience with LangChain, CrewAI, and LangFlow (bonus points for deep expertise). Strong understanding of vector databases (Pinecone, Weaviate, FAISS) and embedding models. Experience building production-ready AI products, ensuring scalability and reliability. Deep knowledge of prompt engineering, tokenization strategies, and data augmentation for LLMs. Familiarity with ML More ❯
City of London, London, England, United Kingdom Hybrid / WFH Options
Ada Meher
with relevant technologies such as OpenAI, LangChain/LangGraph, LlamaIndex Experience with Hugging Face and LoRA/QLoRA for fine-tuning Experience with RAG & Vector DBs eg. FAISS, Weaviate, Pinecone Any experience of MLOps with MLFlow, AWS (SageMaker), CI/CD (GitHub Actions) or similar would be a benefit to an application The employer is well known not only for More ❯
experience building retrieval-augmented AI search solutions. LLM Fine-Tuning: Experience fine-tuning models for domain-specific performance and optimizing inference speed. Vector Search: Knowledge of DataStax Vector Search, Pinecone, FAISS, or Weaviate. Deployment: Familiarity with Docker, Kubernetes, and CI/CD pipelines (GitHub Actions, Jenkins, or similar). Security & Authentication: Strong understanding of OAuth2, JWT, and API security best More ❯
london, south east england, united kingdom Hybrid / WFH Options
Starcom
Data Acumen: Solid understanding of data requirements for machine learning models, including feature engineering, data validation, and dataset versioning. Vector Database Experience: Practical experience working with vector databases (e.g., Pinecone, Milvus, Chroma) for embedding storage and retrieval. Generative AI Familiarity: Understanding of data paradigms for LLMs, RAG architectures, and how data pipelines support fine-tuning or pre-training. MLOps Principles More ❯
