Primary Responsibilities:
- Generative AI Strategy & Execution: Developing and executing strategies that align with broader business objectives, setting clear goals for the team focusing on machine learning solutions.
- Architect and deploy LLMs (GPT, LLaMA, Claude, Mistral), multimodal AI (text, image, video), and AI-powered automation tools.
- Oversee the implementation of retrieval-augmented generation (RAG), prompt engineering, and fine-tuning strategies.
- Work on text, speech, image, and video generation use cases in industries like finance, healthcare, media, and e-commerce.
- Ensure AI solutions are scalable, cost-effective, and optimized for performance.
- Identify high-impact AI use cases across various domains (e.g., AI chatbots, content generation, fraud detection, AI-driven automation).
- Partner with product managers and software engineers to integrate AI into existing and new business applications.
- Monitor AI model performance and continuously optimize based on user feedback and business KPIs.
- Team Management: Building and leading a strong team to develop, deploy, and manage state-of-the-art ML models in production, including classic ML, DNNs, and Large Language Models/GenAI.
- Talent Scouting and Training: Seeking out the best talents in machine learning and data science and overseeing their training.
- Maintaining Best Practices: Staying up to date with emerging AI trends to ensure the organization always utilizes the best ML practices.
- Collaboration: Working collaboratively with teams across the organization and influencing decision-making at senior levels.
- Ethical AI Practices: Ensuring AI/ML solutions are developed and deployed ethically and responsibly, in compliance with applicable laws, regulations, contracts, enterprise policies, and Code of Conduct.
- AI Impacts: Working with stakeholders to align on AI agenda across all lines of business