• fully remote contract

• initially 6 months

• 500 to 525 per day - Inside IR35

Key Skills:

• Design of Gen AI Models

• RAG

• AI/ML Pipelines

The Role:

• Design, prototype, and deploy Generative AI models (LLMs, Transformers, Diffusion models) for enterprise use cases.

• Build and 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 using Python, Java, or Node.js backends.

• Collaborate with architects to define scalable and secure AI service architectures.

Required Experience/Skills:

• Implementing AI/ML pipelines for model training, validation, and deployment (using tools such as MLflow, Vertex AI, or Azure ML).
• Manage model evaluation, drift monitoring, and continuous improvement processes.
• Optimize inference performance and cost (e.g., model compression, quantization, API optimization).
• Ensure compliance with AI 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 AI use cases.
• Contribute to the creation of a strategic AI adoption roadmap and reusable AI Workbench / platform components.
• Support POCs, pilots, and full-scale implementations with agile delivery.