About the role
We are Senior AI Engineers; this means working on some of the hardest problems at the intersection of AI, personalization, and human relationships: building models that understand users deeply, learn from long-term interactions, develop persistent context, and deliver increasingly personalized conversations at scale. This is frontier AI work figuring out how AI learns to know a person and how that person can trust our AI more than anyone else in their world.
Responsibilities:
- Build and own production-grade ML/AI systems end-to-end.
- Develop LLM, RAG, conversational AI, and agentic workflows.
- Work on personalization, memory, recommendations, and user intelligence.
- Build LLM orchestration, evaluation, and optimization systems for quality, latency, and cost.
- Combine structured astrology intelligence with ML, retrieval, and LLM reasoning.
- Work closely with product, backend, and other teams to ship impactful features at scale.
Requirements:
- 3-5 years in ML, applied ML, NLP, or GenAI engineering.
- Strong Python and software engineering fundamentals.
- Hands-on experience with LLMs, RAG, embeddings, vector search, or conversational AI.
- Experience deploying ML/AI systems to production.
- Strong understanding of ML fundamentals, evaluation, APIs, system design, scalability, and cloud.
- Ability to own problems end-to-end: design, build, evaluate, and produce.
Good to Have:
- Experience with LangChain/LangGraph.
- Familiarity with vector databases.
- Work with Hugging Face or open-source LLMs.
- MLOps and LLM evaluation expertise.
- Background in recommendation systems.
- Experience with Indic or multilingual NLP.