• Advanced Modeling & Predictive Analytics: Lead the research, design, and implementation of advanced Machine Learning, Deep Learning, and Time Series Forecasting models to solve complex enterprise business and planning challenges.
• Generative AI Architecture: Architect GenAI solutions, focusing on fine-tuning proprietary and open-source Large Language Models (LLMs) via Transformer architectures for specialized enterprise data tasks.
• Next-Gen Interfaces: Design and integrate Conversational AI and autonomous Agentic AI workflows to create intuitive experiences that can independently execute complex planning tasks.
• Production & Scale: Collaborate with Engineering, Product, and Design teams to transition AI models from early prototypes into robust, highly scalable production systems.
• Technical Leadership: Serve as a core subject matter expert, mentoring cross-functional teams and driving a culture of technical excellence, rigorous testing, and continuous learning.

• Extensive professional engineering experience across Artificial Intelligence, Machine Learning, or related domains.
• Deep technical understanding of Transformer architectures, prompt engineering, and conversational AI patterns, alongside practical experience with autonomous agent frameworks.
• Experience fine-tuning LLMs (e.g., LoRA, QLoRA, RLHF) specifically for domain-specific enterprise applications.
• Taken responsibility for models from concept to production, utilizing strong MLOps and LLMOps practices to ensure scalable, reliable, and monitorable deployments.
• High proficiency in Python and modern software development practices, including rigorous testing, code reviews, and CI/CD pipelines.
• Strong hands-on experience in traditional Machine Learning and deep learning techniques, specifically including Time Series Forecasting algorithms.

• Background in Computer Science, Artificial Intelligence, Statistics, Data Science, or a related quantitative field.
• Experience working with scalable cloud infrastructure (AWS, GCP, or Azure) and MLOps tools for model training, monitoring, and deployment.
• Background in forecasting, planning, or analytics applications
• Familiarity with Anaplan or similar enterprise planning platforms
• Experience with A/B testing and experimentation frameworks for AI features
• Contributions to open-source ML projects or research publications

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