Lead-ML Engineer

📋 Description

• Design and tune a hybrid search engine (vector + lexical search).
• Implement ranking and blending (BGE rerankers, RRF).
• Own end-to-end search accuracy metrics (NDCG, MRR, Recall).
• Build automated accuracy evaluation harness for continuous testing.
• Establish quality benchmarks and metrics-driven culture.
• Lead cross-functional AI/ML projects and mentor engineers.

🎯 Requirements

• Deep hands-on with vector databases (Pinecone, Milvus, Qdrant) and search engines (Elasticsearch
• Proven reranking and fusion techniques (BGE, RRF) in production.
• Experience with load testing (Locust, k6) and diagnosing bottlenecks.
• MDM feed integration and NoSQL (Firestore) experience.
• Strong ML for search relevance and GenAI for retrieval/synthesis.
• 10+ years in ML/AI engineering; AI/ML project leadership.

🎁 Benefits

• Sub-second latency at scale and high-impact ownership.
• Mentorship and cross-functional collaboration opportunities.
• Hybrid work environment in Hyderabad.
• Opportunity to shape core search platform for millions of users.
• Competitive tech stack and data-driven culture.
• Exposure to MDM, data governance, and production-grade Infra.