Machine Learning Engineer II - Autonomous Driving Performance Evaluation

May Mobility is transforming cities through autonomous technology to create a safer, greener, more accessible world. The company is seeking ML-Oriented Software Engineers to measure, analyze, and improve the performance of their Autonomous Driving stack through data and metrics.

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

Requirements:

• 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
• 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)