Key Responsibilities:
- Architect and design robust AI/ML solutions that align with business objectives and user needs.
- Lead the development of Generative AI models and applications, including conversational agents, chatbots, and personalized user experiences.
- Collaborate with cross-functional teams to integrate AI capabilities into Groww’s products and services.
- Stay at the forefront of AI advancements and identify opportunities to leverage emerging technologies.
- Ensure the scalability, performance, and security of AI/ML systems in production.
- Guide and mentor ML engineering teams in best practices for AI/ML development.
- Define AI strategies and roadmaps, balancing short-term impact with long-term innovation.
- Drive the evaluation and selection of tools, platforms, and frameworks for AI projects.
- Work closely with data scientists, product managers, and other stakeholders to translate business problems into AI solutions.
Required Skills and Experience:
- 8-12 years of core machine learning experience, including building and deploying ML models in production.
- Strong expertise in Generative AI, natural language processing (NLP), and conversational AI technologies.
- Proven experience in designing and implementing AI-powered chatbots, virtual agents, or similar applications.
- Proficiency in Python and common ML libraries/frameworks (e.g., TensorFlow, PyTorch, Hugging Face, etc.).
- Hands-on experience with cloud platforms (AWS, GCP, or Azure) and scalable architectures for AI workloads.
- Strong understanding of data pipelines, feature engineering, and MLOps practices.
- Excellent problem-solving skills and a deep understanding of machine learning algorithms.
- Experience in driving AI strategy and delivering measurable business impact.
- Strong communication and stakeholder management skills.
Preferred Qualifications:
- Advanced degree (Master’s or Ph.D.) in Computer Science, Machine Learning, AI, or a related field.
- Familiarity with financial services or fintech domains.
- Experience with reinforcement learning, recommendation systems, or personalization techniques.
- Contributions to open-source projects or research in the AI/ML domain