AI Retrieval & Relevance Engineer

AI Retrieval & Relevance Engineer

Salary: $140,000 (Paid B2B via Deel)

Interview Process: 3 to 4 stages

Work Type: Full Time and Fully Remote

We are seeking an experienced AI Retrieval & Relevance Engineer to architect, implement, and optimise retrieval-augmented generation (RAG) and hybrid search systems that provide accurate, grounded context to LLMs and AI agents.

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, or a related field (or equivalent practical experience).
• Proven experience designing and tuning information retrieval systems, vector search, and RAG frameworks.
• Strong knowledge of vector and hybrid search technologies (e.g., FAISS, Weaviate, Elasticsearch, Milvus, Pinecone, or equivalents).
• Proficiency in Python and familiarity with ML tooling (PyTorch or TensorFlow experience helpful, particularly for rerankers).
• Familiarity with distributed processing and orchestration tools (e.g., Spark, Airflow, Kubeflow) as applied to indexing and evaluation pipelines.

Nice to Have

• Experience with rerankers, learning-to-rank, query understanding, and relevance tuning.
• Background in LLM fine-tuning, prompt engineering, and RAG optimization.
• Familiarity with agentic systems and multi-step retrieval patterns (iterative retrieval, tool-use).
• Cloud platform experience with scalable storage and indexing infrastructure.