Director of Computer Vision & Machine Learning

Director of Computer Vision & Machine Learning

📍 Austin, TX - Onsite

We're looking for an experienced Director of Computer Vision to lead a team responsible for developing advanced vision and perception capabilities for next-generation defense systems. This is a hands-on technical leadership role requiring proven experience managing and developing engineering teams, while providing technical direction across computer vision, perception, AI/ML, and software engineering. You’ll guide the team through the full product lifecycle, from algorithm development and data strategy to system integration, testing, and deployment in operational environments.

What You’ll Be Doing

• Lead the development of advanced computer vision algorithms with a focus on real-time detection, tracking, and classification.
• Design and deploy machine learning models optimized for edge computing - balancing speed, accuracy, and reliability in constrained environments.
• Work closely with hardware teams, especially electrical engineers, to ensure seamless integration of vision systems into our architecture.
• Conduct rigorous testing across a variety of operational scenarios and environmental conditions to validate system performance and robustness.
• Lead engineers and contribute to building a strong internal knowledge base in machine learning, computer vision, and robotics.

What You’ll Bring

• A deep-rooted passion for AI, computer vision, and robotics, with a track record of hands-on exploration and innovation in these areas.
• Bachelor’s degree or higher in Computer Science, Electrical Engineering, or a related field, with a strong focus on machine learning and vision systems.
• 10+ years of experience developing machine learning-based computer vision solutions, ideally within robotics or real-time applications.
• Proven experience leading, mentoring, and developing high-performing engineering teams, with a track record of building strong technical organizations and developing engineering talent.
• Demonstrated success in building and deploying real-world vision systems, especially in time-sensitive or safety-critical contexts.
• Proficiency in Python and C++, along with experience using ML frameworks such as PyTorch, TensorFlow, or similar.
• Solid understanding of embedded systems and the challenges of integrating vision algorithms into hardware platforms.
• Familiarity with sensor technologies like cameras, LiDAR, RADAR, and their application in autonomous systems.