Resumen del rol

Machine Learning Engineer II- Autonomous Driving Performance Evaluation

Requisitos y responsabilidades

Contenido del rol extraído en secciones para revisar más rápido.

Essential 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.

Skills and Abilities

  • 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.

Required

  • Bachelor's or Master's degree in Robotics, Computer Science, Statistics, or a related field with strong mathematical and engineering foundations.
  • A minimum of 2 years building evaluation, metrics, or data analysis systems for ML in production.
  • Proficiency in Python (NumPy/Pandas or equivalent dataframe tooling) with experience in Linux environments.
  • Familiarity with basic concepts in Machine Learning (losses, train/eval splits, common failure modes) and basic Perception and Planning concepts in Autonomous Driving.

Desirable

  • Proficiency in Go or C++.
  • Familiarity with experiment tracking and evaluation tooling such as MLflow, Weights & Biases, or in-house equivalents.
  • Familiarity with statistical methods for A/B comparison, regression detection and noisy-metric analysis.
  • Familiarity with data mining and curation at scale (embedding-based retrieval, active learning, auto-labeling).
  • Familiarity with visualization and dashboarding tools (Plotly, Grafana, Streamlit or similar).

Physical Requirements

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

Details

  • Prolonged sitting
  • Prolonged standing
  • Prolonged computer use

Benefits and Perks

  • Comprehensive healthcare suite including medical, dental, vision, life, and disability plans. Domestic partners who have been residing together at least one year are also eligible to participate.
  • Health Savings and Flexible Spending Healthcare and Dependent Care Accounts available.
  • Rich retirement benefits, including an immediately vested employer safe harbor match.
  • Generous paid parental leave as well as a phased return to work.
  • Flexible vacation policy in addition to paid company holidays.
  • Total Wellness Program providing numerous resources for overall wellbeing
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FocoAutonomy EngineeringÁrea del rol
Señal de seniorityMiddleNivel del candidato
StackPythonSkills principales
Ubicación1 país aceptadoElegibilidad

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