AI Engineer
Location
On-site - Austin, TX
Employment Type
Full‑Time
Job Title
AI Engineer (Junior, Senior, Lead/Principal)
Company Overview
We are a funded startup building autonomous machines for defense markets. Our first product is designed to counter small, fast FPV suicide drones — also known as Group 1 / sUAS, similar to those seen in the Russia‑Ukraine conflict. Our robots require world‑class perception and decision‑making. If you love turning cutting‑edge machine learning into field‑ready capability, this is your playground.
We are currently focused on defensive systems, with the potential to expand into lethal systems in the future.
Position Summary
We are seeking a AI Engineer to join a small, experienced team. You will be the computational “brain” behind our next‑generation counter‑small unmanned aerial systems (c‑sUAS). You will design, develop, and deploy low‑latency machine learning models essential for real‑time detection, tracking, and classification of hostile FPV suicide drones.
This role requires technical mastery to create resilient, autonomous systems that operate under strict size, weight, and power (SWaP) constraints at the defense edge. You should be capable of building models from scratch and have a fundamental understanding of the problem space. We are currently using imitation learning to build a transformer‑based control system, as well as for sensing.
Essential Duties
Design, train, and optimize novel neural network architectures specifically for rapid threat classification (e.g., differentiating hostile drones from environmental clutter).
Implement robust sensor fusion techniques to combine and interpret disparate data streams (radar, RF, acoustic, and optical sensors).
Drive MLOps and edge deployment strategies, ensuring machine learning models are efficiently deployed, monitored, and updated in the field on low‑SWaP hardware.
Apply advanced machine learning techniques, particularly anomaly detection (AD), to ensure the system can adapt to and identify new, custom‑built drone threats not present in the training data.
Collaborate with the robotics and computer vision teams to ensure model output seamlessly translates into real‑time trajectory predictions for interceptor guidance.
Requirements
Programming/frameworks: Non‑negotiable proficiency in Python. Extensive experience with deep learning frameworks such as PyTorch and TensorFlow.
Modeling: Deep understanding of classification models, neural network architectures, and demonstrated experience with sensor fusion.
Lifecycle: Practical experience with the entire machine learning lifecycle, including model optimization for edge deployment and resource‑constrained environments.
Foundations: Strong knowledge of linear algebra, calculus, and statistics necessary for debugging, optimizing, and writing core machine learning algorithms.
Compliance: This position requires access to export‑controlled information under ITAR. Only U.S. persons are permitted to access such information.
Must be willing to submit to a background check.
Nice‑to‑Have
Prior defense startup experience
Security clearance or ability to obtain one
Passion for building robots or engineering projects as a hobby
Benefits
Competitive salary + early equity
Opportunity to build systems the Department of Defense actively needs
New lab equipped with Jetsons, scopes, and 3‑D printers
Direct influence on product and technology roadmap
About the interview
Application screen phone call (30+ min)
Chat with founders (2 x 30 min)
Paid take-home ($500, usually ~4-8 hours)
Review work
Offer
Sponsored
