研究科學家 (機器人領域) Research Scientist (Robotics)

職位概述：

作為研究科學家，您將負責開發最先進的基於深度學習的感知演算法，以提升我們自動駕駛系統的感知能力。

職責：

• 設計並實施最先進的深度神經網路架構和訓練方法，解決物件偵測、車道線偵測、影像分割等複雜的感知任務。
• 開發深度估算、立體視覺 (Stereo Vision)、光流 (Optical Flow) 以及其他與 ADAS 空間理解相關的演算法。
• 研究並開發深度神經網路壓縮策略，在確保效能的同時，優化其在 ASIC 平台上的硬體加速效果。
• 優化和調整網路結構，以滿足嵌入式系統的即時性能需求。
• 持續關注深度學習與電腦視覺領域的最新研究，並實作最先進的技術。
• 提出並探索創新的方法，以提升 ADAS 感知演算法的能力。
• 參與專利申請及研究論文發表，展示在職期間開發的創新解決方案。

Position Overview: 

As the Research Scientist, you will be responsible for developing cutting-edge deep learning-based perception algorithms for enhancing the perception capabilities of our autonomous driving systems.

Responsibilities:

• Design and implement state-of-the-art deep neural network architectures and training methodologies for addressing complex perception tasks, such as object detection, lane detection, and segmentation.
• Develop algorithms for depth estimation, stereo vision, optical flow, and other tasks related to spatial understanding in ADAS.
• Investigate and develop strategies for compressing deep neural networks while maintaining performance, particularly for hardware acceleration on ASIC platforms.
• Optimize and fine-tune network structures to meet real-time performance requirements on embedded systems.
• Stay at the forefront of deep learning and computer vision research by continuously reviewing and implementing state-of-the-art techniques.
• Propose and explore novel ideas and approaches to advance the capabilities of perception algorithms in ADAS.
• Contribute to patent applications and research papers, showcasing the innovative solutions developed during your tenure.

職位要求：

• 計算機科學、電機工程或相關領域的碩士或博士學位。
• 具備深度學習與電腦視覺領域的研究與開發經驗，專注於感知任務。
• 具備設計、訓練及評估深度神經網路進行視覺數據分析的專業能力。
• 熟悉以下一個或多個領域：物件偵測與追蹤、立體視覺 (Stereo Vision)、深度估算、多視角幾何 (Multi-View Geometry)、三維電腦視覺、運動結構 (Structure from Motion)、網路壓縮與優化等。
• 精通 Python，若熟悉 C++ 亦為加分項。
• 具備扎實的數學基礎，尤其是在與電腦視覺及深度學習相關的最佳化技術方面。

Requirements: 

• Master's or Ph.D. in Computer Science, Electrical Engineering, or a related field.
• Proven research and development experience in deep learning and computer vision, with a focus on perception tasks.
• Strong expertise in designing, training, and evaluating deep neural networks for visual data analysis.
• Proficiency in one or more of the following areas: object detection and tracking, stereo vision, depth estimation, multi-view geometry, 3D computer vision, structure from motion, network compression, and optimization.
• Advanced programming skills in Python, with familiarity in C++ being a plus.
• Strong mathematical foundation in optimization techniques relevant to computer vision and deep learning.

Online Interview