Computer Vision Engineer

• Design and deploy machine learning models that perform reliably in resource-constrained, edge environments
• Work closely with hardware and electrical engineers to integrate perception systems into embedded platforms
• Test and validate models across a range of real-world scenarios and environmental conditions
• Contribute to scaling prototypes into robust, field-ready systems
• Support the evolution of the platform across different use cases and operational requirements

• Strong background in computer vision and machine learning, ideally within robotics or autonomous systems
• 4+ years of experience developing and deploying ML-based vision systems
• Experience working on real-time or safety-critical applications
• Proficiency in Python and/or C++, with hands-on experience using frameworks such as PyTorch, TensorFlow, or similar
• Experience deploying models in embedded or edge environments
• Familiarity with sensor systems such as cameras, LiDAR, or radar
• Strong problem-solving mindset and ability to work in cross-functional engineering teams

Nice to Have

• Experience in robotics, autonomy, or defense-related applications
• Exposure to tracking systems, sensor fusion, or control systems
• Background in deploying models to production in constrained environments

• Competitive salary + equity
• Full benefits package (health, dental, vision)
• Paid time off
• Opportunity to work on cutting-edge, real-world autonomous systems

We're working with a highly innovative, venture-backed defense technology startup building next-generation autonomous systems designed to operate in complex, real-world environments. Founded by experienced engineers with a strong track record in robotics and software, the team is developing advanced systems that combine computer vision, machine learning, and control systems to detect, track, and respond to fast-moving aerial threats. This is an opportunity to work on mission-critical technology with real-world impact, within an engineering-led culture that values speed, ownership, and technical excellence.