Computer Vision Engineer

Company Overview Allen Control Systems (ACS) is a cutting-edge defense startup founded by two former Navy electrical engineers with a proven track record in robotics and software. We are developing an autonomous gun turret using advanced computer vision and control systems to precisely detect, track, and neutralize enemy drones. With an engineering-first culture, ACS values technical excellence and innovation. Backed by our founders’ successful exits from two previous ventures acquired for a combined $180M in 2022, we are committed to ensuring that the groundbreaking technologies we develop will have a real-world impact. About The Role We are looking for a Computer Vision and Machine Learning Engineer to develop and optimize the CV/ML systems at the core of our autonomous gun turret, with a focus on real-time drone detection, tracking, and classification. ACS is hiring across multiple experience levels for this role, from Associate through Senior Staff; your title and level will be determined based on your experience, skills, and scope of responsibility. You will work closely with electrical engineers to integrate vision systems into the turret’s hardware architecture and contribute to hardening the prototype into a military-grade system. 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 What You’ll Do Develop and optimize computer vision algorithms for real-time drone detection, tracking, and classification on our autonomous gun turret. Design and implement machine learning models capable of operating in resource-constrained environments while maintaining high accuracy and reliability. Collaborate with electrical engineers to integrate computer vision systems into the turret’s hardware architecture; contribute to hardening the prototype into a military-grade system and developing variants for different weapon systems and engagement ranges. Conduct extensive testing and validation of CV algorithms across diverse scenarios to ensure robustness and performance under varying environmental conditions. What You’ll Need 4+ years of experience in machine-learning-based computer vision, ideally in the context of robotics or autonomous systems; Bachelor’s degree or higher in Computer Science, Electrical Engineering, or a related field with a strong focus on ML and computer vision. Proven track record developing and deploying computer vision systems, ideally in real-time or safety-critical applications; deep passion for ML, computer vision, and robotics with roots that go back to early in your career. Proficiency in Python and C++; hands‑on experience with ML frameworks such as PyTorch, TensorFlow, or similar. Experience with embedded systems and integrating CV algorithms into hardware; familiarity with sensors such as cameras, LiDAR, and radar and their integration into autonomous systems. You’ll Stand Out Experience with object detection and tracking in challenging real-world conditions such as small targets, cluttered backgrounds, or low-contrast imagery. Background in defense, aerospace, or autonomous systems where performance and reliability requirements are non‑negotiable. Experience deploying and optimizing models on edge hardware such as NVIDIA Jetson or similar embedded GPU platforms. Experience with multi-sensor fusion or integrating data from heterogeneous sensor modalities such as optical and infrared cameras. 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. #LI-AS1 #J-18808-Ljbffr