Join our team to build next-generation AI-powered perception systems for autonomous robotics operating in challenging real-world environments. You will design, develop, and optimize computer vision and machine learning solutions for real-time deployment on embedded platforms.
Key Responsibilities:
- Design and develop computer vision pipelines for object detection, segmentation, and multi-object tracking.
- Build and optimize deep learning models for real-time inference.
- Develop data annotation, validation, and dataset management pipelines.
- Perform model optimization, hyperparameter tuning, and performance benchmarking.
- Deploy AI models on embedded platforms such as NVIDIA Jetson.
- Optimize inference using TensorRT, CUDA, and mixed-precision techniques.
- Debug and improve perception pipelines for accuracy, latency, and reliability.
- Collaborate with software, robotics, and system integration teams.
Skillset:
- 3–5 years of experience in Computer Vision and Machine Learning.
- Strong knowledge of Python and/or C++.
- Hands-on experience with PyTorch or TensorFlow.
- Strong understanding of OpenCV, image processing, and deep learning.
- Experience with object detection, image segmentation, and tracking algorithms.
- Familiarity with CNNs, Vision Transformers, and model optimization techniques.
- Experience with NVIDIA Jetson, TensorRT, CUDA, or similar embedded AI frameworks.
- Understanding of stereo vision, depth estimation, and real-time AI deployment is an advantage.
Qualifications
- Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, Computer Vision, or a related field.
- Experience developing production-grade AI solutions for real-world applications.
- Strong debugging, analytical, and problem-solving skills.
If this role is found exciting to you, email your CV to [email protected]
