Senior Staff Engineer / Data Scientist, Simulation & Evaluation
July 24
🏢 In-office - Bay Area
Description
• Develop simulation based evaluation workflows - combining data, metrics & simulation methodologies - to provide clear performance assessment of Xpeng's autonomous driving system, influence and drive onboard development based on evaluation insights. • Develop simulation based metrics across safety, comfort, efficiency and compliance dimensions. • Conduct data mining from vast amount of owned and customers' driving logs to feed evaluation and development needs. • Collaborate with onboard and AI teams to build machine learning models to automate evaluation processes, improve data relevancy, and advance simulation technologies such as smart agents. • Act as a key person connecting simulation and onboard. Produce actionable feedback for onboard development based on rigorous evaluation, enable rapid & effective development iterations. • Play a key role in shaping next generation simulation and evaluation methodologies as onboard transitions to End-to-End autonomous driving stack.
Requirements
• Master or Ph.D. in Mathematics, Statistics, Physics, Computer Science, or a related technical field. • 5+ Years of experience in software engineer / engineering data scientist / machine learning engineer roles. Solid engineering skills with excellent data fluency. • Proficiency in C++ or Python. • Experience with statistical analysis, data mining and machine learning. • Excellent problem-solving skills, ability to think critically with analytical mindset. • Demonstrated success in working with complex engineering / ML systems involving big data and challenging quantitative problems. • Strong communication skills, both verbal and written, to effectively convey technical concepts and processes.
Benefits
• A fun, supportive and engaging environment • Opportunity to make significant impact on transportation revolution by the means of advancing autonomous driving • Opportunity to work on cutting edge technologies with the top talent in the field • Competitive compensation package • Snacks, lunches and fun activities
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