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Autonomous Driving Algorithm & Systems Engineer

Ambarella · Taiwan Hsinchu · Taiwan

Employer
Ambarella
Requisition id
Autonomous-Driving-Algorithm---Systems-Engineer_JR100378
First posted (employer ATS)
(5d ago)
First seen by this site
2026-10-01T00:16:38Z
Last verified live
2026-10-06T01:47:44Z
Source
Employer career portal (workday)

Job description

AI Vision Processors For Edge Applications Our solutions make cameras smarter by extracting valuable data from high-resolution video streams. Job Description Our autonomous driving technology stack spans multiple core modules, including Perception (Detection / Tracking), Localization, Motion Forecasting, Planning, and Real-Time Map Generation (RTMG). We are looking for engineers with expertise in any of these areas to join our team and help build robust, production-grade autonomous driving systems. (This role does not require a single person to handle all modules; responsibilities will be assigned based on technical specialization.) Key responsibilities: 1. Design, implement, and optimize algorithms across modules such as Perception (object detection, classification, tracking), Prediction, Planning, Localization, and RTMG. 2. To comply with ISO 21448 (SOTIF) requirements, validate all inputs by verifying data formats, timing and synchronization, coordinate alignment, and fallback mechanisms for missing or degraded sensor data across camera, ego-motion (ODOM), radar, and lidar. 3. Collaborate with teams including systems and software to integrate algorithms into the autonomous driving stack and deliver robust system-level solutions. Job Requirements: 1. Education background: Master degree or Ph.D degree 2. Minimum experience: At least one year of relevant work or academic experience 3. Similar or other experiences: - Experience of autonomous driving algorithm would be a plus - Experience of model deployment would be a plus - Experience of model optimization such as pruning and quantization would be a plus 4. Skills - Strong in autonomous driving algorithms or related system integration. - Background in machine-learning-based computer vision or large language model (LLM) technologies. - Familiar with machine learning frameworks such as PyTorch, TensorFlow, etc. - Proficient in Python and C/C++ programming.

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