Machine Learning Engineer II - Autonomous Driving Performance Evaluation Anywhere, USA

May Mobility; Ann Arbor (MI); On-site; USD 100,000 - 130,000; Full time

Benefits offered by this job

Comprehensive healthcare suite

Rich retirement benefits

Flexible vacation policy

Job summary

May Mobility in Ann Arbor, Michigan, is seeking a Machine Learning Engineer II to join their Autonomous Driving team. The role involves designing metrics and evaluation pipelines for their innovative autonomous vehicles.

Candidates should have a strong background in robotics or autonomous technologies, proficiency in Python, and experience in data analysis systems. The position offers a dynamic environment with opportunities to influence the future of transportation.

Qualifications

• Minimum of 2 years of experience in ML data analysis systems.
• Familiarity with machine learning concepts and basic statistics.
• Experience in production Linux environments.

Responsibilities

• Designing ML metrics and evaluation pipelines.
• Building and maintaining test and regression suites.
• Improving models through data analysis and error mining.

Skills

Quantitative metrics design

Statistical analyses

Dataset slicing

Hard-example mining

Data balancing

Education

Bachelor's or Master's in relevant fields

Tools

Python

Go

C++

MLflow

Plotly

Job description

Machine Learning Engineer II - Autonomous Driving Performance Evaluation

Anywhere, USA

May Mobility is transforming cities through autonomous technology to create a safer, greener, more accessible world. Based in Ann Arbor, Michigan, May develops and deploys autonomous vehicles (AVs) powered by our innovative Multi-Policy Decision Making (MPDM) technology that literally reimagines the way AVs think.

Our vehicles do more than just drive themselves - they provide value to communities, bridge public transit gaps and move people where they need to go safely, easily and with a lot more fun. We’re building the world’s best autonomy system to reimagine transit by minimizing congestion, expanding access and encouraging better land use in order to foster more green, vibrant and livable spaces. Since our founding in 2017, we’ve given more than 500,000 autonomous rides to real people around the globe. And we’re just getting started. We’re hiring people who share our passion for building the future, today, solving real‑world problems and seeing the impact of their work. Join us.

Job Summary

May Mobility is entering an exciting phase of growth as we expand our first‑of‑its‑kind autonomous shuttle and mobility services across the nation. Launched in 2017 with a strong team of experienced roboticists and software engineers with decades of experience fielding robotic systems in the wild, May Mobility is looking to expand its team of robotics engineers with a background in robotics or autonomous vehicles.

We are seeking ML‑Oriented Software Engineers with experience in robotics applications. As part of our Autonomous Driving ML team, you will use ML Engineering concepts to measure, analyze and systematically improve the performance of May’s Autonomous Driving stack through data, metrics, evaluation and test/hillclimbing suites.

• 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.

Qualifications and Experience

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.
• 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

Travel required? Low 5‑10%

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 resources for overall wellbeing

May Mobility is an equal opportunity employer. All applicants for employment will be considered without regard to race, color, religion, sex, national origin, age, disability, sexual orientation, gender identity or expression, veteran status, genetics or any other legally protected basis. If you believe you will need an accommodation, please let us know. Any information you share about gender pronouns, ethnicity, veteran status or disability is voluntary and will be kept confidential and will not impact the hiring decision.