Senior Machine Learning Engineer

Senior Machine Learning Engineer (Search, Recommendations & Conversational AI) Location: Remote Role Type: Senior IC (P3+) Team: Discovery – Search, Recommendations & AI Experiences Urgency: Immediate (pre–IPL launch milestones) About the Role We are building next-generation conversational search , personalized recommendations , and AI-driven discovery for one of India's largest entertainment ecosystems. This role is for a hands-on ML Engineer who can design, train, and productionize models powering search relevance, retrieval, personalization, and LLM-based conversational experiences at massive scale. You will work closely with backend, platform, and catalog enrichment teams to deliver high-quality ML components under tight performance and latency constraints. Key Responsibilities Build and improve search ranking , retrieval , and query understanding models. Develop ML components for Conversational Search : Multi-turn context handling Query intent detection and classification Retrieval-augmented generation (RAG) pipelines Reasoning workflows (ReAct, static + dynamic agent flows) Design and optimize embedding models , vector stores, and similarity search systems. Build personalized ranking and recommendation models using deep learning. Work on large-scale ML systems optimized for: Low latency High throughput Cost-efficient inference Implement ML pipeline best practices (versioning, monitoring, A/B testing, observability). Collaborate with platform teams to integrate ML services across search, recommendations, and conversational agents. Develop caching strategies (prompt cache, vector cache, similarity caching) to hit strict SLA targets. Contribute to long-term roadmap: foundational retrieval models, multi-objective optimization, user lifecycle modeling. Required Qualifications 4–10 years of experience in Machine Learning / Applied ML engineering . Strong foundations in ML, deep learning, Transformers, and neural retrieval. Hands-on experience with: Search systems (retrieval + ranking) Recommendation models Embedding models & vector databases TensorFlow / PyTorch Proven experience building production-grade ML systems at scale. Familiarity with LLMs, RAG architectures, prompt engineering, and agent workflows. Strong coding skills (Python) and experience with modern ML stack (TensorFlow, PyTorch, Faiss/ScaNN, Triton, etc.). Ability to work closely with backend teams to deploy models in distributed systems. Excellent problem-solving skills and comfort working on ambiguous, high-impact problems. Preferred Qualifications Experience with conversational AI , chat-based retrieval, or multi-turn dialog modeling. Experience in media, streaming, sports data or large catalog discovery. Knowledge of micro-drama, short-video personalization, or multi-objective recommendation systems. Strong understanding of scalability patterns: batching, async orchestration, caching layers. Why Join Work on flagship launches (World Cup → IPL) impacting hundreds of millions of users. Solve some of the most challenging problems in search, discovery, and conversational AI at scale. Collaborate with a world-class team building foundational discovery platforms for India's largest digital ecosystem.