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Allen Control Systems

Computer Vision & Machine Learning, Associate

Reposted Yesterday
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In-Office
Mountain View, CA, USA
94K-154K Annually
Junior
In-Office
Mountain View, CA, USA
94K-154K Annually
Junior
Develop and optimize real-time computer vision algorithms and ML models for an autonomous anti-drone turret. Integrate CV systems with embedded hardware and sensors, conduct testing and validation across environments, and help harden prototypes into military-grade systems and variants for different weapons and ranges.
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Associate Computer Vision & Machine Learning for Autonomous Anti-Drone Systems

Company Overview:

 

Allen Control Systems (ACS) is a cutting-edge defense startup, founded by two ex-Navy electrical engineers with a proven track record in robotics and software. We are developing a small, autonomous gun turret that employs advanced computer vision and control systems to precisely target and neutralize small drones and loitering munitions. Our innovative approach requires overcoming significant technical challenges, making this an exciting and dynamic environment for experienced engineers.

With an engineering-first culture, ACS values technical excellence and innovation. Backed by our founders' successful exits from two previous venture acquired for a combined $180M in 2022, we are committed to ensuring that the groundbreaking technologies we develop will have a real-world impact. 

We’re hiring across multiple experience levels, including:

  • Associate CV/ML Engineer

  • CV/ML Engineer

  • Senior CV/ML Engineer

  • Staff CV/ML Engineer

  • Senior Staff CV/ML Engineer

    Your title and level will be determined based on your experience, skills, and the scope of responsibility appropriate for the role.

 

What You'll Do:

  • 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.

What You'll Need:

  • 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.

  • 0-3+ 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.

What We Offer:

  • Competitive salary

  • ACS Equity Package

  • Health, Dental, Vision Insurance

  • Paid Time Off

Allen Control Systems is an Equal Opportunity Employer, providing equal employment opportunities to all employees and applicants for employment. Allen Control Systems prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.

 

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