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.
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
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.
- Applying data-centric ML methods such as hard-example mining, resampling/reweighting and curriculum or balance adjustments to lift model performance.
Qualifications and Experience
Candidates most successful in this role typically hold the following qualifications or comparable knowledge or 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.
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
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 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!
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. Below, you have the opportunity to share your preferred gender pronouns, gender, ethnicity, and veteran status with May Mobility to help us identify areas of improvement in our hiring and recruitment processes. Completion of these questions is entirely voluntary. Any information you choose to provide will be kept confidential, and will not impact the hiring decision in any way. If you believe that you will need any type of accommodation, please let us know.
Note to Recruitment Agencies: May Mobility does not accept unsolicited agency resumes. Furthermore, May Mobility does not pay placement fees for candidates submitted by any agency other than its approved partners.
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