Description review

Machine Learning Engineer II - Autonomous Driving Performance Evaluation

May Mobility · United States · back to the listing

HR standards

59/100

needs work

Title ↔ description

82/100

solid

Reads as

Machine Learning Engineer

99% confident

What this role officially is

data scientist — ESCO, the EU occupation classification

Data scientists find and interpret rich data sources, manage large amounts of data, merge data sources, ensure consistency of data-sets, and create visualisations to aid in understanding data. They build mathematical models using data, present and communicate data insights and findings to specialists and scientists in their team and if required, to a non-expert audience, and recommend ways to apply the data.

Also known as: data scientists, data engineer, research data scientist, data expert, data research scientist

How others title the same work

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What the listing never says

  • 25 bullet points. Long requirement lists deter qualified candidates, who read them as hard gates. Scope clarity
  • No location or timezone policy stated, so a candidate cannot tell where they may work from. Scope clarity

The listing, marked up

Nothing in the wording of this listing tripped a check. The scores above still judge how complete and coherent it is.

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.

Salary Range

$172,000—$210,000 USD

May Mobility uses automated tools to support — but not replace — human judgment in our recruiting process, to find out more please click here

Originally posted on Himalayas

How this was produced

Highlights are found by rule, not by a model: each one is a phrase matched at a known position, and every note is a template we wrote. The two scores come from a typed-decision model (Jev) that reads the listing against the official role definition and real listings for the same role, and returns probabilities rather than prose — it never writes any of the words on this page, and never chooses what to highlight.

Deterministic penalty applied to the HR score: 8 points (from 67 before penalties). Reviewed 21 Sep 2026.