OverviewWe\''re seeking a highly skilled Machine Learning Engineer (RAG Specialist) to join our AI hyperscaler client on a 6–12 month contract. You will play a critical role in designing, building, and optimizing Retrieval-Augmented Generation (RAG) systems to support cutting-edge large language model (LLM) solutions at scale. This position offers a unique opportunity to work with advanced infrastructure and collaborate with world-class AI teams on next-generation machine learning systems.

Responsibilities

Design, implement, and optimize RAG pipelines for large-scale AI/ML deployments.

Develop and maintain data ingestion, retrieval, and indexing workflows across distributed environments.

Work with vector databases, embeddings, and information retrieval systems to ensure high performance and low latency.

Collaborate with researchers, ML engineers, and data scientists to integrate RAG into production-grade LLM applications.

Contribute to scaling and deployment strategies across a hyperscaler environment (cloud-native).

Monitor, debug, and fine-tune ML pipelines for robustness and efficiency.

Produce high-quality documentation and knowledge transfer for internal stakeholders.

Required skills and experience

Proven expertise in RAG (Retrieval-Augmented Generation) techniques and real-world implementation.

Strong experience with LLMs, transformers, and embeddings.

Hands-on experience with vector databases (e.g., FAISS, Pinecone, Weaviate, Milvus, Vespa).

Deep knowledge of Python and modern ML/AI frameworks (e.g., PyTorch, Hugging Face, LangChain, LlamaIndex).

Strong background in distributed systems, data pipelines, and cloud-native environments (Azure, AWS, or GCP).

Previous work with AI hyperscalers or large-scale ML infrastructure is highly desirable.

Excellent problem-solving skills, with the ability to optimize systems for performance and scalability.

Employment terms

Duration: 6–12 months (initial term with potential extension)

Location: Hybrid – London-based (1 day onsite per week)

Rate: Up to £1100 per day (Inside IR35)

Start Date: Immediate / ASAP

Apply now to join our innovative client and contribute to a fast-paced, dynamic environment.

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