About the Role

• Lead the design, development, and deployment of novel agentic systems and core machine learning models that power AI-driven capabilities.
• Execute data analysis, error analysis, and rigorous experimentation to drive model improvements and new capability development.
• Design and implement the end-to-end machine learning pipeline (MLOps), ensuring model scalability, reliability, and consumption via robust APIs.
• Work with large-scale datasets to perform data wrangling, feature engineering, and validation to train and fine-tune state-of-the-art models.
• Apply machine learning and distributed systems principles in production to address model scalability, concurrency, fault tolerance, and performance challenges.
• Own ML models and systems through their full lifecycle, including deployment, monitoring, debugging, and ongoing operational improvements.

About You

Basic Qualification: 8+ yea...