Computer Vision Engineer
Posted Jun 28 · 137 applicants
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The role in plain words
- 4+ years of professional experience in Computer Vision and algorithms development
- Deep mastery of Classic CV (image filtering, feature extraction, geometry) alongside modern Deep Learning
- Proven track record in Object Detection, Image Classification, and Object Tracking in dynamic environments
- Python
- PyTorch
- Proficiency in C / C++ for performance-critical modules
- Strong command of Linux, Docker, and Arm-based systems
- Implement ML pipelines for audio feature extraction and classification
- Knowledge of Video Streaming protocols and low-latency video processing (RTSP, GStreamer)
Extracted from the job description · kept up to date automatically
Who this suits
Full job description
Original listing · kept for referenceWe’re looking for a Computer Vision Engineer to join a cutting-edge team driving R&D innovation in radar-based systems. In this role, you will lead the end-to-end development of Computer Vision models, from data strategy and model training to deployment in real-world defense applications.
Key Responsibilities
• Algorithm Development: Design and implement robust algorithms for real-time detection, classification, and tracking of objects.
• End-to-End Pipeline: Develop CV pipelines that combine classic image processing techniques with state-of-the-art Deep Learning models.
• Edge Optimization: Port and optimize models for Edge Deployment.
• Data Reliability: Build tools for automated data collection in changing environments.
• Skills: Problem Solver, Team Player.
Qualifications
• Experience: 4+ years of professional experience in Computer Vision and algorithms development.
• Computer Vision Fundamentals: Deep mastery of Classic CV (image filtering, feature extraction, geometry) alongside modern Deep Learning.
• Model Specialization: Proven track record in Object Detection, Image Classification, and Object Tracking in dynamic environments.
• Software Toolkit: Expert-level proficiency in Python, PyTorch, and OpenCV. with a strong understanding of Linux/ARM architectures
Preferred Qualifications
• Programming: Proficiency in C / C++ for performance-critical modules.
• Environment: Strong command of Linux, Docker, and Arm-based systems.
• Audio Signal Processing: Implement ML pipelines for audio feature extraction and classification.
• Streaming: Knowledge of Video Streaming protocols and low-latency video processing (RTSP, GStreamer).
Questions about this role
- This listing did not state a salary. We only show pay when the employer publishes it.
- 4+ years of professional experience in Computer Vision and algorithms development, Deep mastery of Classic CV (image filtering, feature extraction, geometry) alongside modern Deep Learning, Proven track record in Object Detection, Image Classification, and Object Tracking in dynamic environments, Python, PyTorch