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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. We are seeking Machine Learning Leaders in the Autonomous Vehicle domain. As part of our team, you will play a critical role in enhancing May’s Machine Learning capabilities both on and off the vehicle, in a commercial large-scale environment with high standards of quality. Essential Responsibilities Design, train and evaluate state of the art models for May’s autonomous driving, simulation and ML Platform stack. Leverage emerging techniques in the End-to-End driving, Vision Language Action (VLA), World or Foundation model domains to solve commercial-scale problems. Lead small teams of cross functional Engineers beyond the state of the art. Define data balance, training experiment and evaluation practices to train efficiently at petabyte scale. Skills and Abilities Success in this role typically requires the following competencies: Direct experience architecting & training VLA, MMLM, or Generative World Models for commercial-scale applications Experience composing, processing and characterizing large (>100TB) multi-modal datasets Experience analyzing and addressing long-tail failure cases in large models Experience leading teams of 2-3 Engineers and communicating technical details to interdisciplinary leadership. Qualifications and Experience Candidates most successful in this role typically hold the following qualifications or comparable knowledge or experience: Required Extensive practical experience in one of the following domains: Vision Language Action Models Generative World Models Foundation Models in Robotics Data Centric AI A minimum of 4 years of industry experience working on commercial robotics systems. A minimum of 1 year mentoring ML Engineers in a commercial or lab environment. Master’s degree in Robotics, Computer Science, or Computer Engineering, or a field that requires a strong mathematical and/or engineering foundation. Practical experience handling the “Long Tail” problem in Machine Learning. Strong programming skills in Python/PyTorch in a Linux environment. Functional understanding of LiDAR, Camera and Radar processing techniques. Desirable PhD and/or published research in the described specialty domains. Familiar with common post-training techniques. Experience deploying models to resource constrained and edge hardware Functional understanding of C/C++/CUDA memory and threading models. 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%
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.