About the job
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 (Re Act, 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 Tensor Flow / Py Torch • 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 (Tensor Flow, Py Torch, Faiss/Sca NN, 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.
Requirements
- Machine Learning
- Search Systems
- Deep Learning
- Recommendation Models
Preferred Technologies
- Machine Learning
- Search Systems
- Deep Learning
- Recommendation Models
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