Job Description
Staff Machine Learning Scientist – Search (Conversational AI & Gen AI)
Role Description
As a Staff Machine Learning Scientist in Nykaa’s Search team, you will lead the architectural vision for our next-generation discovery experience. You will be responsible for transforming keyword-based search into a sophisticated conversational ecosystem, leveraging Gen AI, Large Language Models (LLMs), and agentic workflows. This is a high-impact leadership role where you will define the 1–2 year technical roadmap, architecting systems that understand complex beauty and fashion intent through natural dialogue to guide users from discovery to purchase.
What are we looking for?
Education: Bachelor’s, Master’s, or Ph D in Computer Science, Machine Learning, NLP, or a related quantitative field.
Experience:
7+ years of hands-on industry experience in Machine Learning and Natural Language Processing.
Proven track record of leading and deploying large-scale AI systems in high-traffic production environments (e.g., Search, Recommendations, or Virtual Assistants).
Demonstrated experience in taking ambiguous product visions and translating them into scalable technical architectures.
Technical Skills:
Generative AI & LLMs: Expertise in fine-tuning (SFT, RLHF), prompt engineering, and optimizing open-source models (e.g., Llama, Mistral) for domain-specific tasks.
Agentic Workflows: Deep understanding of multi-agent systems, tool-use, and autonomous planning frameworks (e.g., Lang Chain, Llama Index, or Auto GPT).
Retrieval-Augmented Generation (RAG): Mastery of semantic search, vector databases (e.g., Pinecone, Milvus), and hybrid retrieval strategies.
NLP Foundations: Strong grasp of Transformers, attention mechanisms, and classical NLP tasks (NER, Intent Classification).
Engineering Excellence: Proficiency in Python, distributed training, and high-performance inference optimization (e.g., v LLM, Tensor RT-LLM).
Soft Skills:
Technical Mentorship: Proven ability to guide and grow senior and mid-level scientists across multiple squads.
Strategic Influence: Ability to partner with VP-level stakeholders to drive the long-term AI strategy for the organization.
Responsibilities
Architectural Leadership: Design and lead the implementation of a multi-agent conversational search system capable of planning and executing complex user requests.
LLM Strategy: Oversee the full lifecycle of domain-specific model development, from data curation and fine-tuning to low-latency deployment.
Advanced RAG Systems: Architect state-of-the-art retrieval pipelines that combine structured product data with unstructured content to provide factually accurate, conversational responses.
Strategic Roadmap: Define and own the technical roadmap for AI-driven discovery, balancing cutting-edge research with immediate business impact.
Mentorship & Quality: Set the standard for technical excellence through high-level design reviews, research leadership, and mentoring MLS-2 and MLS-3 scientists.
Cross-Functional Leadership: Partner with Product, Engineering, and Business leads to redefine the user discovery journey through Gen AI-first features.
What You’ll Learn & Grow Into
Shaping the AI-first future of one of India's largest e Commerce platforms.
Leading organizational-level technical strategy as a Principal Scientist or Distinguished Engineer.
Mastering the operationalization of multi-agent AI systems at a scale of millions of daily active users.
Role Description
As a Staff Machine Learning Scientist in Nykaa’s Search team, you will lead the architectural vision for our next-generation discovery experience. You will be responsible for transforming keyword-based search into a sophisticated conversational ecosystem, leveraging Gen AI, Large Language Models (LLMs), and agentic workflows. This is a high-impact leadership role where you will define the 1–2 year technical roadmap, architecting systems that understand complex beauty and fashion intent through natural dialogue to guide users from discovery to purchase.
What are we looking for?
Education: Bachelor’s, Master’s, or Ph D in Computer Science, Machine Learning, NLP, or a related quantitative field.
Experience:
7+ years of hands-on industry experience in Machine Learning and Natural Language Processing.
Proven track record of leading and deploying large-scale AI systems in high-traffic production environments (e.g., Search, Recommendations, or Virtual Assistants).
Demonstrated experience in taking ambiguous product visions and translating them into scalable technical architectures.
Technical Skills:
Generative AI & LLMs: Expertise in fine-tuning (SFT, RLHF), prompt engineering, and optimizing open-source models (e.g., Llama, Mistral) for domain-specific tasks.
Agentic Workflows: Deep understanding of multi-agent systems, tool-use, and autonomous planning frameworks (e.g., Lang Chain, Llama Index, or Auto GPT).
Retrieval-Augmented Generation (RAG): Mastery of semantic search, vector databases (e.g., Pinecone, Milvus), and hybrid retrieval strategies.
NLP Foundations: Strong grasp of Transformers, attention mechanisms, and classical NLP tasks (NER, Intent Classification).
Engineering Excellence: Proficiency in Python, distributed training, and high-performance inference optimization (e.g., v LLM, Tensor RT-LLM).
Soft Skills:
Technical Mentorship: Proven ability to guide and grow senior and mid-level scientists across multiple squads.
Strategic Influence: Ability to partner with VP-level stakeholders to drive the long-term AI strategy for the organization.
Responsibilities
Architectural Leadership: Design and lead the implementation of a multi-agent conversational search system capable of planning and executing complex user requests.
LLM Strategy: Oversee the full lifecycle of domain-specific model development, from data curation and fine-tuning to low-latency deployment.
Advanced RAG Systems: Architect state-of-the-art retrieval pipelines that combine structured product data with unstructured content to provide factually accurate, conversational responses.
Strategic Roadmap: Define and own the technical roadmap for AI-driven discovery, balancing cutting-edge research with immediate business impact.
Mentorship & Quality: Set the standard for technical excellence through high-level design reviews, research leadership, and mentoring MLS-2 and MLS-3 scientists.
Cross-Functional Leadership: Partner with Product, Engineering, and Business leads to redefine the user discovery journey through Gen AI-first features.
What You’ll Learn & Grow Into
Shaping the AI-first future of one of India's largest e Commerce platforms.
Leading organizational-level technical strategy as a Principal Scientist or Distinguished Engineer.
Mastering the operationalization of multi-agent AI systems at a scale of millions of daily active users.
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