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What you will be doing:
Lead process and infrastructure improvements to increase efficiency and effectiveness of the DriveOS teams
Modernize our toolchain to enable fast, measurable, quality engineering
Work closely with our Program Management team to capture data needed to make better decisions
Consult with and counsel senior management and teams on highly complex technical issues to achieve program level alignment
Analyze & diagnose the underlying events contributing to these metrics, identify trends, and resolve top priority engineering work toward improving the platform experience
Drive implementation and/or recommend improvements across features and throughout the stack, in collaboration with the corresponding component engineering teams.
Ensure that the driving quality of the fleet engineering remains optimized by making go/no-go decisions on major technical changes, defining the tests/frameworks required to guard against regressions, andidentifying/addressingregressions.
What we need to see:
Bachelors or a higher degree (or equivalent experience) in Computer Science or a related field, or strong technical work history
15+ years of experience in a similar or related role and meaningful experience in automotive software development field
Practical experience in developing embedded software, using version control systems, and debugging
Well-rounded knowledge of how an autonomous vehicle stack works, and practical experience dealing with the challenges in this area
Strong leadership and interpersonal skills, with the ability to drive alignment across large organizations
Ways to stand out from the crowd:
Experience with autonomous vehicle and/or machine learning development
Background with data analysis tools/languages
Experience with Generative AI tools (LLMs)
Experience with start-ups and/or early-stage products
You will also be eligible for equity and .
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