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Zoox

Senior Software Engineer - Autonomy Safety Metric

Data Engineering
Foster City, CAHybridFull-time

About this role

We are seeking a highly skilled and experienced engineer to join the Behavior Evaluation team and play a pivotal role in measuring the safety of Zoox’s autonomous driving technology. The Behavior Evaluation is the team behind the behavioral part of Zoox’s estimate, quantifying how often the autonomy stack causes the vehicle to stop unexpectedly and how that maps to collision risk. As a member of this team, you will own and scale the pipeline behind these numbers, driving innovation in ML model scoring, sampling, and projections while making the system faster, more reliable, and easier to audit. You will work closely with a team of talented engineers and researchers in a fast paced, collaborative environment as Zoox expands to more cities and software releases.

In this role, you will:

  • Build and maintain the Behavior Evaluation data pipelines (PySpark/zspark medallion architecture on Databricks, EMR Serverless and Airflow) that produce weekly per-geofence estimates.

  • Turn the statistical method (sampling, triage weights, mileage sharing, projections) into tested, reproducible code with checks that fail loudly when the data is bad.

  • Build tools that cut the manual work in each weekly run.

  • Work with cross functional stakeholders so the methodology is applied consistently in code and in clearance reports.

  • Help adapt to new release methodologies and new geofences.

    • Qualifications:

  • 7 - 9 Years of experience or 5+ years with a strong data-platform track record 

  • Expert Python, with production experience in PySpark/Spark and Pandas

  • Experience designing scalable batch data pipelines: orchestration, Delta/lakehouse tables, idempotent backfills

  • Solid grounding in applied statistics: sampling, weighting, estimators, confidence intervals

  • Strong testing and CI habits for data code

    • Bonus Qualifications:

  • Experience with autonomous-vehicle simulation, safety metrics or triage workflows

  • Experience putting ML models into production in a data pipeline 

  • Experience with Databricks and AWS (EMR Serverless, S3)

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