Allen Control Systems

Computer Vision & Machine Learning Engineer, Mid-Level

Austin, TX
✓ Verified live on the employer's own system · added 453 days ago
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Mid-level · 4+ yrs exp

Requirements

Education: Bachelor's degree or related field

Experience: 4+ years

Skills & tools

Machine LearningElectricalPythonC Plus PlusEmbedded
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Full job description

- Development and optimization of computer vision algorithms for our autonomous gun turret, focusing on real-time drone detection, tracking, and classification.

- Design and implement machine learning models that can operate in resource-constrained environments while maintaining high accuracy and reliability.

- Collaborate closely with electrical engineers to integrate computer vision systems into the turret's hardware architecture.

- Conduct extensive testing and validation of computer vision algorithms in various scenarios to ensure robustness and performance under different environmental conditions.

- Contribute to the hardening of the prototype turret into a military-grade system, and assist in developing variants for different weapon systems and engagement ranges.

- Deep passion for machine learning, computer vision, and robotics, and have been exploring these areas since early in your career.

- At least a Bachelor's degree in Computer Science, Electrical Engineering, or a related field, with a strong focus on machine learning and computer vision.

- 4-7 years of experience working on machine-learning-based computer vision, ideally in the context of robotics.

- A proven track record of developing and deploying computer vision systems, ideally in real-time or safety-critical applications.

- Proficient in Python, C++, and have experience with machine learning frameworks such as TensorFlow, PyTorch, or similar.

- Experience with embedded systems and integrating computer vision algorithms into hardware.

- Familiar with various sensors (e.g., cameras, LIDAR, RADAR) and their integration into autonomous systems.

- You enjoy collaborating with other engineers to solve complex technical challenges.

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