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
Senior 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
Apply: Add your résumé, GitHub/portfolio, and a brief note on a project you’re proud of to!
Don’t meet every bullet? If you build robots for fun and learn fast, we want to hear from you.
