Director of Computer Vision and Machine Learning

Allen Control Systems•Austin, TX

21h

About The Position

Allen Control Systems (ACS) is a defense technology company developing precision robotic systems for the United States and its allies. Its Bullfrog autonomous precision weapon system converts existing weapons into counter-drone systems. ACS is headquartered in Austin, Texas, with additional operations in Alexandria, Virginia; Mountain View, California; and Huntsville, Alabama. The Director of Computer Vision and Machine Learning bridges executive AI strategy and day-to-day technical execution for Bullfrog’s perception and tracking systems. The role translates the VP / Chief Engineer of AI’s vision into priorities, roadmaps, and standards for the Computer Vision, Machine Learning, and Tracking teams while remaining hands-on with code, data, and technical problem-solving. The director also works with executive leadership and engineering leaders across the company, representing CV/ML/Tracking in technical and schedule discussions.

Requirements

10–15 years of experience in computer vision and/or machine learning.
At least 3 years leading managers or multiple teams.
Bachelor’s degree in Computer Science, Electrical Engineering, Robotics, or a related field.
Deep expertise in at least one of object detection, multi-object tracking, sensor fusion, or deep learning for perception.
Strong Python programming skills and familiarity with C++ and common frameworks including PyTorch, TensorRT, and OpenCV.
A proven track record taking computer vision/machine learning systems from research through production deployment.
Demonstrated success collaborating across software, mechanical, electrical, and systems disciplines to deliver complex products on schedule.
Excellent communication skills with staff engineers, peers, and C-level executives.
Comfort operating in a flat, collaborative, low-ego, high-ownership organization.

Nice To Haves

Master’s or PhD in Computer Science, Electrical Engineering, Robotics, or a related field.
15–20 years of experience leading managers across multiple teams, including experience scaling computer vision/machine learning organizations beyond a single team.
Experience with real-time or embedded perception systems, including model optimization and edge deployment.
Familiarity with tracking algorithms such as Kalman filters and data association methods.
Familiarity with MLOps practices, large-scale training pipelines, and data engineering.
Systems engineering experience, including requirements decomposition, interface definition, and verification.
Experience in autonomous systems, robotics, defense, surveillance, or sports analytics.
Publications, patents, or open-source contributions in the field.

Responsibilities

Translate the VP / Chief Engineer of AI’s vision and technical strategy into actionable plans, milestones, and priorities for the CV, ML, and Tracking teams; communicate direction to the teams and report status, risks, and insights upward.
Manage, coach, and develop the CV/ML and Tracking team managers, holding them accountable for delivery, performance, and team health.
Mentor engineers and technical leads and help identify and develop future leaders.
Partner with software, mechanical, electrical, and systems engineering to address cross-disciplinary problems, including sensor selection and placement, optics, compute and power constraints, and thermal limits.
Own on-time delivery of CV/ML and Tracking contributions to program schedules; anticipate integration risks, drive their resolution, and escalate schedule risks when needed.
Establish and enforce standards for model development, evaluation, experiment tracking, reproducibility, and documentation.
Define measurable metrics and benchmarks, including detection accuracy, tracking performance, latency, and robustness.
Review code and pull requests, and write code, prototypes, or analysis scripts to unblock the team or validate approaches.
Participate in architecture and design reviews, challenge assumptions, and guide teams toward robust, scalable solutions.
Represent CV/ML/Tracking in technical and schedule discussions with other VPs, Chief Engineers, and executive leadership.