About the Role:
As a Senior Data Scientist with expertise in Natural Language Processing (NLP) and advanced AI techniques to join our dynamic team. In this pivotal role, you will drive the development of cutting-edge solutions involving retrieval-augmented generation (RAG), large language models (LLMs), and agentic AI for our innovative bots platform. You will leverage your deep knowledge and experience to tackle complex challenges, deliver impactful results, and shape the future of conversational AI technology.
The Impact You Will Create
You will not just be building models; you will be reshaping how users interact with technology. Your work will directly result in:
- Massive Scale: Building a state-of-the-art conversational servicebot designed to scale seamlessly across 1 million+ Monthly Active Users (MAU).
- Next-Gen User Experience: Serving real-time insights to customers through a cutting-edge conversational UI/UX that processes millions of streaming data points.
- Advanced Automation: Developing production-grade AI/ML solutions to solve complex Text2Action problems and analyzing time-series data to detect anomalous behavior instantly.
Responsibilities:
• Strategic Problem Solving: Identify and define critical business problems that can be addressed
through advanced machine learning and NLP techniques. Translate complex requirements into
actionable data science projects.
•Advanced Model Development: Design, develop, and deploy sophisticated NLP models, including
LLMs and retrieval systems, for applications such as answer generation and conversational AI. Utilize
RAG methodologies to enhance model performance and accuracy.
•Algorithmic Expertise: Apply your deep understanding of machine learning algorithms, statistical
methods, and mathematical principles to create innovative solutions that address real-world
problems and drive user engagement.
• Collaboration and Leadership: Partner with product managers, engineers, and business stakeholders
to understand requirements, define success metrics, and ensure alignment with business objectives.
Lead cross-functional teams to deliver end-to-end solutions.
• System Architecture and Scalability: Oversee the integration of machine learning models into
production systems. Collaborate with engineering teams to build scalable, high-performance data
pipelines and ensure robust deployment of models in live environments.
• Research and Innovation: Stay at the forefront of research in NLP, AI, and related fields. Contribute to
the advancement of the company's technology stack and explore new methodologies to maintain a
competitive edge in the industry.