• Master's or PhD in a quantitative field such as Data Science, Computer Science, Statistics, or a related discipline
• 10+ years of experience in Machine Learning, with a focus in vision
• 5+ years proven success in technical leadership, while delivering impactful projects across the organization
• Strong expertise in machine learning algorithms, and data analysis techniques
• Proficiency in Python, with hands-on experience using machine learning libraries and frameworks such as Pytorch, Tensorflow, or JAX
• Strong communication and collaboration skills, with the ability to effectively convey technical concepts to both technical and non-technical stakeholders in a fast-paced context
• Experience and familiarity with production ML environments, including model release, evaluation and monitoring

Desirable

• We are looking for a world-class engineering leader to manage a team of talented Machine Learning engineers and researchers driving the development & innovation of our vision technology
• Leveraging cutting-edge techniques, you will play a vital role in our overall success in deploying state of the art AI capabilities all around the globe
• Lead and manage a high-performing team of machine learning engineers in a fast-paced environment, providing technical guidance, mentorship, and support to drive their professional growth and development
• Oversee the rapid development and implementation of machine learning models, leveraging advanced algorithms and techniques to optimize performance
• Collaborate closely with cross-functional teams, including product managers, software engineers, and data engineers, to deliver data-driven insights and recommendations that enhance our solutions in an agile environment
• Stay at the forefront of industry trends, emerging technologies, and best practices in machine learning, vision and MLOps. Apply this knowledge to drive innovation, meet tight deadlines, and maintain a competitive edge
• Establish and maintain strong relationships with stakeholders, providing clear communication of technical concepts and findings to both technical and non-technical audiences