Lead AI/ML Engineer

Skills: Senior lead with broad understanding of AI space and expertise in creating/ holding executive briefings.

12+ years of experience with a high-level individual contributor or lead researcher responsible for architecting the core intelligence of a product

·       Architectural Leadership: Design and lead the development of end-to-end ML systems, from data ingestion to MLOps orchestration and real-time inference.

·       State-of-the-Art (SOTA) Implementation: Stay ahead of the curve in Generative AI, Computer Vision, or NLP, adapting the latest research papers into production-ready features.

·       Optimization & Scaling: Solve complex bottlenecks related to model latency, cost-efficiency (e.g., quantization, pruning), and large-scale distributed training.

·       Technical Mentorship: Review code and model architectures, setting the standard for rigorous testing, evaluation frameworks, and Responsible AI practices.

Cross-Functional Strategy: Partner with Product and Engineering leads to determine the technical feasibility of "moonshot" AI features

1.      Languages: Expert-level Python, C++, or Java.

2.      Frameworks: PyTorch, TensorFlow, JAX.