Senior Machine Learning Engineer (Search, Recommendations & Conversational AI)
Location: Remote
Role Type: Senior IC (P3+)
Team: Discovery Search, Recommendations & AI Experiences
Urgency: Immediate (preIPL 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
- 410 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.
