1.Responsible for the R&D of algorithms related to tactile/force sensors, including signal processing, feature extraction, modeling, and optimization.
2.Build, train, and optimize tactile models based on frameworks like PyTorch.
3.Participate in sensor data acquisition, processing, annotation, and the development of related toolchains.
4.Collaborate with Backend/SDK/UI teams to integrate algorithms into products.
Write technical documentation and algorithm specifications, promote internal knowledge accumulation and external dissemination (e.g., technical blogs, papers, open-source contributions).
5.Track academic and industrial frontiers, exploring applications of Reinforcement Learning / VLA (Vision-Language-Action) Models / Multimodal Perception in tactile sensors.
1.Bachelor's degree or above in Computer Science, Automation, Electronics, Mathematics, Robotics, or related fields.
2.Solid Python programming skills, with good coding standards and engineering practices.
3.Familiarity with common computer vision algorithms (e.g., detection, segmentation, feature extraction) and relevant experimental experience.
4.Proficient in Data Structures & Algorithms, understanding basic time/space complexity analysis.
5.Experience with networks and robotics hardware (e.g., ROS, RPC).
6.Understand the underlying mechanisms of PyTorch (computation graph, autograd, optimizers), capable of independently training and tuning models.
Preferred Qualifications
1.Experience contributing to/maintaining open-source projects (e.g., GitHub, GitLab, personal technical blog).
2.Strong research spirit, proactive problem-solving ability, possessing a geek spirit and self-motivation.
3.Experience related to robotics/sensors/embedded systems, with an understanding of hardware data flow processing.
4.Familiarity with deep learning deployment optimization (e.g., ONNX, TensorRT, edge deployment).
5.Strong mathematical modeling skills (Probability Theory, Optimization, Signal Processing).
Note: This position is also recruiting interns in parallel.
