About the role
This role is designed for a perception engineer who can build, evaluate, and deploy the sensing and embedded vision systems that allow our autonomous intercept platforms to detect, track, and act on fast-moving aerial threats.
You will work across the full perception stack, from camera and lens selection through image formation, signal processing, embedded deployment, model evaluation, and integration with the autonomy system. Machine learning is part of the job, but not the whole job. We are looking for someone who understands that perception performance starts before the model: with the sensor, optics, scene, exposure, motion, latency, compute, and data pipeline.
You will support camera and lens trade studies, evaluate sensor characteristics against mission requirements, develop image- and signal-processing techniques that improve detection of small, low-contrast objects, and help translate range data into better embedded perception performance. This is not a research-only role. Your work will run onboard real vehicles, integrate with the autonomy stack, and be tested against demanding field data.
We are looking for evidence-driven engineers: individuals who prioritize physical reality over opinion, care about end-to-end system performance, and can debug problems across the full chain from photons hitting the sensor to detections reaching the autonomy system.
This is a strong fit for someone who wants to build perception systems that leave the laptop, run on embedded compute, and directly determine whether an autonomous system succeeds in the real world.
What you'll do
You will develop and deploy the optical sensing, image-processing, and embedded perception capabilities that enable our autonomous systems to detect, classify, track, and reason about fast-moving aerial targets in real time.
You will focus on problems in all of the following areas:
- Optical Sensor & Lens Trade Studies: Support camera and lens trade studies, evaluating sensor characteristics such as pixel size, sensitivity, noise, dynamic range, resolution, and optical performance against application requirements.
- Image & Signal Processing: Develop and evaluate image- and signal-processing techniques, including denoising, filtering, temporal extraction, and contrast enhancement, to improve detection of small, low-contrast objects.
- Aerial-Object Data Collection: Design and execute data-collection experiments for aerial-object detection and tracking, then use field data to improve the next system iteration.
- Embedded Vision Deployment: Deploy, benchmark, and maintain perception software on embedded edge compute aboard autonomous vehicles.
- Real-Time Performance: Optimize perception pipelines for latency, throughput, and reliability on NVIDIA Jetson Orin-class hardware using tools such as CUDA and TensorRT where appropriate.
- Computer Vision & ML Models: Design, train, fine-tune, and evaluate vision models for detection, classification, tracking, and state estimation on fast-moving aerial targets.
- Autonomy Stack Integration: Integrate perception outputs into our autonomy stack using ROS 2 and write production-quality C++ for real-time processing.
- End-to-End Debugging: Debug problems across the entire stack, from photons hitting the sensor to detections reaching the autonomy system.
- Performance Characterization: Analyze perception performance across flight data, edge cases, false positives, false negatives, latency, lighting, motion blur, vibration, target size, and engagement conditions.
- Cross-Functional Development: Work closely with autonomy, GNC, state estimation, flight test, electrical, and data teams to ensure perception outputs are useful, timely, and aligned with the needs of the full system.
- Dataset Improvement: Help identify data gaps, improve labeling workflows, and guide future data collection so perception development reflects the environments and target behaviors that matter most.
Basic Qualifications
- Education: BS in Computer Science, Robotics, Electrical Engineering, Computer Engineering, Aerospace Engineering, or a related field plus 1+ years of industry or applied robotics experience, or an MS in a related discipline.
- Perception or Computer Vision: Experience developing perception, computer vision, image-processing, or sensor-processing systems for real-world applications.
- Software Skills: Proficiency in C++ for performance-sensitive systems.
- Image Processing: Familiarity with image-processing fundamentals such as filtering, denoising, contrast enhancement, feature extraction, or temporal analysis.
- Embedded or Real-Time Systems: Experience building, profiling, or deploying software where latency, compute, or hardware constraints matter.
- Computer Vision Models: Experience training, fine-tuning, or evaluating vision models, including CNNs, Vision Transformers, detection, tracking, or related approaches.
- Execution Tempo: Ability to work in a fast-paced engineering environment where field data, hardware constraints, and measured system performance drive rapid iteration.
Preferred Qualifications
Experience in any of the following areas is a plus:
- Camera & Lens Evaluation: Experience evaluating cameras, lenses, image sensors, or optical systems against application requirements.
- Sensor Characteristics: Familiarity with sensor characteristics such as pixel size, sensitivity, noise, dynamic range, resolution, exposure, and optical performance.
- Embedded Edge Deployment: Experience deploying perception software or models on embedded edge platforms, including Jetson Orin or Xavier.
- GPU Optimization: Hands-on GPU programming or profiling experience, including CUDA, TensorRT, or related tools.
- ROS 2: Experience with ROS 2 nodes, lifecycle management, QoS, custom interfaces, or related robotics middleware.
- Sensor Fusion: Experience with sensor fusion, including visual-inertial odometry, camera + radar, camera + LiDAR, or related multimodal perception systems.
- Field Robotics or UAS Testing: Prior field-robotics or UAS test experience.
- Dataset & Evaluation Workflows: Experience building or using datasets, labeling workflows, evaluation metrics, and model regression tools for perception systems.
- Production CV Systems: Experience taking perception algorithms or models beyond notebooks into deployed, maintainable software systems.
Export Control
This position may involve access to technology, material, technical data, defense articles, or information subject to U.S. export-control laws, including the International Traffic in Arms Regulations (ITAR), the Export Administration Regulations (EAR), and applicable contract requirements. Assignment to covered work is contingent upon the company’s ability to verify that the candidate is authorized to receive access to such items or information, including by qualifying as a “U.S. person” as defined in 22 C.F.R. § 120.62, or through any required export-control authorization, notice, approval, or access-control process.
EEO
Askari Defense, Inc. is an Equal Opportunity Employer. We do not discriminate based on race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, age, or any other characteristic protected by law.