Computer Vision & Machine Learning, Staff
Allen Control Systems8 months ago
Responsibilities
- Lead development and optimization of real-time computer vision algorithms for drone detection, tracking, and classification.
- Design and implement accurate, reliable machine learning models for resource-constrained environments.
- Integrate computer vision systems with turret hardware in collaboration with electrical engineers.
- Test and validate algorithms across varied environmental scenarios for robustness and performance.
- Help harden the prototype turret into a military-grade system and develop variants for different weapon systems and engagement ranges.
- Mentor junior engineers and grow the company’s machine learning and computer vision expertise.
Requirements
- At least a master's degree in Computer Science, Electrical Engineering, or a related field focused on machine learning and computer vision.
- At least 9 years of experience working on machine-learning-based computer vision, ideally in robotics.
- A proven track record developing and deploying computer vision systems, ideally for real-time or safety-critical applications.
- Proficiency in Python and C++, with experience using machine learning frameworks such as TensorFlow or PyTorch.
- Experience with embedded systems and integrating computer vision algorithms into hardware.
- Familiarity with cameras, LIDAR, RADAR, and their integration into autonomous systems.
- Ability to mentor and collaborate with engineers on complex technical challenges.
Benefits
- ACS Equity Package
- Health, Dental, and Vision Insurance
- Paid Time Off
Categories
About Allen Control Systems
Allen Control Systems builds AI-enabled robotic weapon stations and small autonomous gun turrets that retrofit legacy and modern weapons for precise targeting, with emphasis on counter‑UAS missions. It sells hardware and software systems to U.S. defense and national security customers and integrators. The privately held company is headquartered in Austin, Texas, with an office in Alexandria, Virginia, and was founded by two former Navy electrical engineers.