Machine Learning Engineer II - Autonomous Driving Performance Evaluation

Job description

Job responsibilities

• Design, implement and own ML metrics and evaluation pipelines spanning offline model evaluation, simulation and on-road performance.
• Build and maintain test, regression and hillclimbing suites that gate model and stack releases, including automated triage of regressions to root cause.
• Drive model improvement through loss analysis, error mining, and data balancing/curation strategies for training and evaluation sets.
• Designing quantitative metrics and statistical analyses that translate model behavior into actionable, decision-grade signals (significance, slicing, long-tail analysis).
• Building evaluation and analytics frameworks in production, including dataset slicing, result aggregation and dashboarding at scale.
• Applying data-centric ML methods such as hard-example mining, resampling/reweighting and curriculum or balance adjustments to lift model performance.

Job requirements

• Standard office working conditions which includes but is not limited to:
• Prolonged sitting
• Prolonged standing
• Prolonged computer use