Bachelor's degree or equivalent practical experience
8 years of experience in software development and with data structures/algorithms.
5 years of experience building and architecting large-scale, production quality Machine Learning (ML) systems.
5 years of experience in distributed development and large-scale data processing.
Experience coding in either C++ or Python.
Experience with ML fundamentals, algorithms, and techniques, including supervised, unsupervised, and reinforcement learning, and experience in areas like natural language processing (NLP), computer vision, and generative AI.
Preferred qualifications:
Experience with generative models (e.g., diffusion models, GANs, transformers) for various media formats (e.g., text, image, video, audio), including prompt engineering, fine-tuning, and evaluation techniques.
Experience with RL algorithms and frameworks, including policy gradient methods, Q-learning, and actor-critic architectures.
Experience building and leading high-performing research or engineering teams, fostering a positive and inclusive culture.
Experience being published in ML/AI conferences or journals, demonstrating a strong research background and ability to communicate complex technical concepts effectively.
Familiarity with agent-based architectures, tool use, reinforcement learning, and techniques for evaluating and optimizing agent behavior.