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 modelsEmbedding models & vector databasesTensorFlow / PyTorchProven 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.