Job Description
- Job Description:
- Designing end2end solutions for Perception and AV stack to enable road network detections across various driving environments from complex intersections to rural curvy roads to multi-level highways.
- Applied research and development of innovative deep learning models for lane graph construction, road boundary detection, traffic element recognition, and other static-world tasks.
- Develop generalizable approaches to support diverse ODDs and Country/region expansion
- Drive and prioritize data-driven development by working with large data collection and labeling teams to bring in high value data to improve perception system accuracy.
- Productize the developed perception solutions by meeting product requirements for safety, latency, and SW robustness.
- Requirements:
- PhD with 4+ years, MS with 6+ years, or BS with 8+ years of relevant experience in Computer Science, Computer Engineering, or a related technical field.
- 2+ years of technical leadership demonstrating high technical and organizational complexity is a big plus.
- Hands-on work experience in developing deep learning and algorithms to solve sophisticated real world problems, and proficiency in using deep learning frameworks (e.g., PyTorch).
- Experience in data-driven development and collaboration with data and ground truth teams.
- Strong programming skills in python and/or C++.
- Benefits:
- equity
- benefits
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