Head of Computer Vision
RainesDev
- San Francisco, CA
- Permanent
- Full-time
- Technical Leadership – Define and execute the computer vision roadmap, from research to large-scale production deployment.
- Model Development – Architect and optimize models for video processing, object detection, and activity recognition, ensuring robustness in real-world conditions.
- Pipeline & Infrastructure – Oversee design and scaling of ML pipelines, including edge computing and integration with proprietary hardware.
- Product Integration – Work with product and hardware teams to align CV capabilities with end-user requirements and operational goals.
- Team Building – Recruit, mentor, and grow a high-performing computer vision engineering team.
- Innovation & Research – Keep the organization at the forefront of CV advancements, publishing and patenting as opportunities arise.
- 7+ years of experience in computer vision and machine learning, with at least 3 years in a high-growth startup or leading projects at a top-tier tech company.
- Proven track record of taking ML/CV projects from initial concept to production with measurable business impact.
- Strong background in video analysis, object detection, and tracking in production environments.
- Hands-on experience with CV frameworks such as PyTorch, TensorFlow, and OpenCV.
- Expertise in edge computing, hardware/software integration, and scaling video analytics solutions.
- Advanced degree (M.S./Ph.D.) in Computer Science, Electrical Engineering, or related field.
- Published work in leading CV/ML conferences (CVPR, ICCV, NeurIPS) or significant patents in the field.
- Applications of CV in autonomous systems, robotics, or applied AI fields.
- Building unique, large-scale labeled datasets and leveraging them for competitive advantage.
- Leading multi-disciplinary teams that bridge the gap between research and field deployment.
- Equally comfortable in the weeds coding and at the whiteboard setting strategic direction.
- Driven by real-world impact, especially in industries where technology adoption is accelerating.
- Operate with first-principles thinking and bring humility, curiosity, and a bias for action.
- Excited to work hands-on in the lab and on-site to see your technology in action.