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
Efforts will include data collection prioritization and planning, labeling prioritization, labeling efficiency optimization, so that value of data is maximized
Leverage data simulation and augmentation for solving extreme scenarios
Productize the developed perception solutions by meeting product requirements for safety, latency, and SW robustness

Requirements

2+ years of technical leadership demonstrating high technical and organizational complexity
10+ years of 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++
Outstanding communication and teamwork skills as we work as a tightly-knit team, always discussing and learning from each other
MS/PhD in CS, EE, sciences or related fields (or equivalent experience)

Benefits

equity
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Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

deep learningalgorithmslane graph constructionroad boundary detectiontraffic element recognitiondata simulationdata augmentationprogramming in Pythonprogramming in C++data-driven development

Soft Skills

technical leadershiporganizational complexitycommunicationteamwork

Certifications

MS in Computer SciencePhD in Computer ScienceMS in Electrical EngineeringPhD in Electrical Engineering