Deep Learning Engineer

About the role

Deep Learning Engineer building production computer-vision models for agricultural robotics, including laser-weeding perception, model optimization, data/evaluation pipelines, and field deployment. Seattle office role with four days on-site; sponsorship is unstated.

Requirements

• 2-4 years professional experience designing novel production computer-vision architectures
• 2-7 years experience in deep-learning model optimization and deployment
• BS+ in computer science, machine learning, or related field, or equivalent experience
• Deep-learning mathematics and modern object detection expertise
• PyTorch and C++ for performance-critical model development and deployment
• Experience across software stack, ideally sensor integration and web services
• Autonomous driving, ADAS, sensor fusion, and real-time outdoor inference are valued

What you'll do

• Develop and validate deep-learning architectures for agricultural computer vision
• Own model optimization and deployment pipelines
• Lead end-to-end ML data, experimentation, evaluation, and production workflows
• Establish best practices and partner with engineering and product
• Mentor engineers and communicate model tradeoffs

Where this was posted

• LinkedIn

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