Data Science Manager

About the Role

Join an innovative engineering company that is redefining industrial AI through cutting-edge computer vision technologies. As a Data Science Manager, you will lead a talented team of 6–8 engineers, drive impactful projects, and contribute to the company's rapid growth trajectory. This role offers a unique opportunity to blend technical leadership with hands-on problem-solving in a dynamic start-up environment.

Responsibilities

• Oversee the comprehensive computer vision strategy, managing everything from data strategy to model deployment and monitoring.
• Architect solutions addressing complex vision challenges, such as novel defect detection and real-time inference in challenging environments.
• Stay updated with the latest advancements in computer vision research and implement relevant models to enhance production capabilities.
• Establish and uphold engineering best practices for model training, data management, and CI/CD processes within the vision stack.
• Optimize inference performance through advanced techniques, ensuring efficiency across various computational platforms.
• Mentor and guide a team of engineers, fostering an atmosphere of continuous learning and innovation.
• Facilitate the hiring and onboarding processes to elevate the team's technical competency and expertise.
• Collaborate with cross-functional teams to align engineering efforts with business objectives and stakeholder needs.

Requirements

• Proven expertise in computer vision technologies and their applications in industrial environments.
• Strong experience with image and video processing techniques, as well as relevant libraries like Albumentations.
• Familiarity with model deployment processes and edge computing for real-time applications.
• Solid understanding of machine learning frameworks and techniques.
• Ability to effectively communicate technical concepts to both technical and non-technical stakeholders.
• A history of managing or leading engineering teams, emphasizing collaboration and knowledge sharing.
• Experience with performance optimization strategies in neural networks.
• A track record of successfully delivering complex projects under tight deadlines.

Nice to Have

• +Experience with advanced computer vision models such as YOLO and Vision Transformers.
• +Knowledge of data versioning tools and experiment tracking platforms.
• +Familiarity with cloud-based GPU services and edge devices.
• +An understanding of agile methodologies and sprint planning processes.
• +Exposure to various industrial domains including steel, cement, and pharmaceuticals.