May Mobility - Machine Learning Engineer II - Autonomous Driving Performance Evaluation
Requirements
• Success in this role typically requires the following competencies: • 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. • Candidates most successful in this role typically hold the following qualifications or comparable knowledge or experience: • 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). • Standard office working conditions which includes but is not limited to: • Prolonged sitting • Prolonged standing • Prolonged computer use
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.
Benefits
• 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 • Don’t meet every single requirement? Studies have shown that women and/or people of color are less likely to apply to a job unless they meet every qualification. At May Mobility, we’re committed to building a diverse, inclusive, and authentic workforce, so if you’re excited about this role but your previous experience doesn’t align perfectly with every qualification, we encourage you to apply anyway! You may be the perfect candidate for this or another role at May. • Want to learn more about our culture & benefits? Check out our website!
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