Engineering Manager, ML Vision and Multimodality

• 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.

• Master's or PhD in a quantitative field such as Data Science, Computer Science, Statistics, or a related discipline.
• 8+ years of experience in Machine Learning, with a focus in vision.
• 2+ years proven success in leading and managing a team of 5 or more ML engineers, driving their professional growth and delivering impactful projects.
• 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.

Preferred Qualifications

• Track record of published ML papers and/or blogs.
• Track record of engagement with open-source ML community.
• Experience with Vision applications in AI for Science, Oil and Gas, or medical imaging.
• Experience with Vision and Multi-modal foundation models such as Stable Diffusion, ViT and CLIP.
• Experience with performance optimization of ML models.
• 2+ years of experience in a startup environment.