Staff Engineer, Machine Learning

Key Responsibilities:

• Design and run AI product runtime services including orchestration, session/state management, policy enforcement, and tool integration. - Implement end-to-end retrieval and memory pipelines for document ingestion, chunking, embeddings, vector indexing, hybrid search, re-ranking, caching, freshness, and deletion semantics. - Productionize ML workflows ensuring strong online/offline parity, feature and metadata services, model contracts, and evaluation instrumentation. - Own performance, reliability, and cost optimization across latency, throughput, cache efficiency, and infrastructure. - Ensure observability-by-default through tracing, structured logging, metrics, guardrails, and resilient fallback paths. Qualifications Required:

• 6-10 years of backend engineering experience. - 2-3 years of experience delivering ML/AI-backed products such as search, recommendations, ranking, or RAG systems. - Practical understanding of embeddings, retrieval quality, evaluation metrics, and data drift. - Deep expertise in distributed systems. - Ability to independently design, build, deploy, and operate systems in fast-paced environments. - Bonus experience includes agentic runtimes, tool-calling patterns, vector databases (FAISS, Milvus, Pinecone, Elasticsearch), Kubernetes-based platforms, modern observability stacks, and privacy-aware data handling. Role Overview: As a Backend Engineer at BharatIQ, you will be responsible for building and operating the core AI/ML-backed systems that drive consumer experiences at scale. Your role will involve designing and managing AI product runtime services, implementing retrieval and memory pipelines, and productionizing ML workflows with a focus on performance, reliability, and cost optimization. You will be expected to bring 6-10 years of backend engineering experience, with a strong background in delivering ML/AI-backed products and deep expertise in distributed systems. Key Responsibilities: