About us: We are an international defence startup, rapidly expanding to support the Ukrainian national needs. As a startup, we operate in a highly flexible environment where agility, adaptability, and a hands-on approach are critical for success..
Key Responsibilities:
- Assist in developing computer vision models for defense and aerospace applications, including DSP, object detection, classification, tracking, and navigation tasks;
- Support implementation and testing of perception pipelines using signal, video, and, where applicable, audio data.
- Help with dataset preparation and data analysis for model training and evaluation.
- Contribute to running experiments, evaluating model performance, and documenting results.
- Assist in deploying and testing models on edge devices (e.g., Jetson, RPi5) under guidance from senior engineers.
- Collaborate with team members (software, hardware, and research) to integrate and test perception components.
- Maintain code, write clear documentation, and follow established development practices.
Required Qualifications:
- Bachelor’s degree (completed or in progress) in Computer Science, Electrical Engineering, or a related field.
- 1-2 years of experience in computer vision, machine learning, digital signal processing, or related areas (internships, coursework, or personal projects count).
- Proficiency in Python and/or C++
- Strong familiarity with the underlying physical concepts of signal and image acquisition and processing
- Familiarity with at least one deep learning or computer vision framework (e.g., PyTorch, OpenCV, Matlab).
- Understanding of fundamental digital signal processing, computer vision concepts (e.g., image processing and deep learning basics).
- Willingness to learn, take feedback, and work in a collaborative team environment.
Nice to Have
- Exposure to signal processing, video processing, robotics, drones, or embedded systems through projects or coursework.
- Experience working in Linux environments.
- Familiarity with version control systems (e.g., Git).
- Interest in real-time systems, edge AI, or multi-sensor data.
- Experience with small personal or academic ML/CV projects (e.g., GitHub portfolio).