Driving Scenario Specialist
Location: Foster City, CA
Reasonable market rate
About the Role
As a Driving Scenario Specialist, you will be at the forefront of annotating and enriching data to teach our Foundation Models how to perceive, predict, and navigate the complexities of the real world. This isn''t just data entry—it is a high-judgment role that requires you to analyze intricate driving environments, identify subtle behavioral cues, and translate human driving intuition into structured data that our engineers can use to build the future of autonomy.
You will serve as a vital link between the physical road and our software stack, ensuring that the "ground truth" we provide our models is nuanced, accurate, and technically sound.
Key Responsibilities
● High-Level Scenario Analysis: Evaluate complex driving data (video, LiDAR, and sensor logs) to provide expert judgment on actor intent, environmental hazards, and social driving norms.
● Engineering Liaison: Actively collaborate with Foundation Model engineers to refine annotation guidelines. You will be responsible for raising "edge case" concerns and identifying gaps in data and tools.
● Thorough Documentation: Create thorough, descriptive narratives of driving sequences, ensuring that every edge case is documented with precision and clarity.
● Data Quality Ownership: Use a suite of internal AI tools and spreadsheets to manage, audit, and validate large datasets, ensuring the highest standards of thoroughness.
● Iterative Feedback Loops: Participate in regular "calibration" sessions with technical teams to ensure your qualitative judgments align with model requirements.
Qualifications
● Education: Bachelor’s Degree (BA/BS) in a field that requires analytical thinking, documentation, or technical communication.
● Driving Expertise: A valid Driver’s License and substantial real-world driving experience (3+ years). You must have a deep, intuitive understanding of road rules, defensive driving, and "unwritten" social cues on the road.
● Communication: Exceptional verbal and written communication skills. You can explain why a specific driving maneuver was risky or optimal to a technical audience.
● Critical Thinking: The ability to look at a 10-second clip and identify the "hidden" dangers that a standard sensor might miss.
● Tech Savviness: Proficiency with Google Sheets/Excel and a high level of comfort learning proprietary AI labeling software and internal data tools.
● Attention to Detail: An almost obsessive focus on thoroughness. You believe that if the data isn''t perfect, the model isn''t safe.
Bonus Points If...
● You have experience in data annotation, QA, or technical writing.
● You have a background in linguistics, cognitive science, or urban planning (fields that deal with complex systems).
● You have an interest in the "how" of machine learning and are eager to see how your labels directly impact model performance.
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