idle Robotics is a Bengaluru-based startup with the ambitious mission to become the intelligence layer powering all autonomous systems. We believe the future of AI is physical, and the first step is giving machines the ability to perceive the world. We are building a foundational layer of visual intelligence that is, in effect, the visual cortex for robots, allowing them to perceive, navigate, and act intelligently. Our dual-use approach means you will contribute to high-impact work, from GPS-denied navigation for defence drones to scalable software for global industrial automation. If you are passionate about robotics, computer vision and pushing the boundaries of Physical AI, we invite you to build the core technology with us.
Role Summary
This track prioritises the architectural training of segmentation and detection models to advance our foundational layer of visual intelligence.
Responsibilities
- Develop and train deep learning architectures like YOLO, Faster RCNN, and UNet for perception tasks.
- Assist in adapting foundation models such as CLIP, DINO, and SAM for robotic use cases.
- Maintain experiment logs and conduct failure analysis on model performance metrics.
- Apply TorchVision and Albumentations within Python workflows for model augmentation.
Minimum Qualifications
- Technical proficiency in PyTorch or TensorFlow frameworks
- Rigorous understanding of probability, calculus, and linear algebra
- Exposure to vision-language or self-supervised models is advantageous
Why Build With Us
- Collaborate directly with IIT/IISc founders in a high-density engineering setting.
- Solve complex zero-to-one problems in Physical AI and autonomous systems.
- Develop dual-use technology for national defence (GPS-denied navigation) and industrial automation.
- Access competitive compensation, paid time off, and a growth-focused culture.
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