Application Guide
How to Apply for Lead ML/Perception Engineer
at May Mobility
🏢 About May Mobility
May Mobility is pioneering the deployment of autonomous electric vehicles designed for safe, sustainable, and eco-friendly transportation. Their focus on robust perception in adverse conditions and commitment to real-world impact make them a standout in the AV industry. Working here means contributing to a fleet that navigates complex urban environments, prioritizing safety and sustainability.
About This Role
As Lead ML/Perception Engineer, you will own the technical direction of perception systems, from scene detection to architectural evolution. Your work will directly influence how the vehicle understands its environment, especially under sensor degradation or bad weather. This role is critical for ensuring the safety and reliability of autonomous operations across the fleet.
💡 A Day in the Life
A typical day might start with a stand-up to review perception performance from overnight fleet data, then diving into code reviews for a new scene detection feature. After lunch, you might analyze edge cases from adverse weather logs and brainstorm fallback strategies with the team, before wrapping up with a design doc for the next architectural update.
🚀 Application Tools
🎯 Who May Mobility Is Looking For
- Experienced in production-grade perception systems for autonomous vehicles or robots, with 5+ years writing high-quality C/C++/Python code.
- Proven track record in developing or fine-tuning large-scale multi-modal models (e.g., vision-language models) for real-world perception tasks.
- Deep familiarity with sensor degradation and adverse weather robustness, including graceful degradation and fallback strategies.
- Strong leadership skills with experience driving architectural changes that improve scalability, latency, and maintainability.
📝 Tips for Applying to May Mobility
Highlight specific projects where you improved perception robustness under adverse conditions (e.g., snow, rain, sensor failure) with measurable results.
Showcase your experience with multi-modal models by detailing how you integrated them into a real-time system, including latency and scalability considerations.
Tailor your resume to emphasize leadership in architectural evolution—mention any refactoring or system redesigns you led.
Include metrics: e.g., improved detection accuracy by X% in low-visibility scenarios, reduced latency by Y ms.
Research May Mobility's approach to safety and sustainability (e.g., their 'minimal risk condition' strategies) and mention alignment in your cover letter.
✉️ What to Emphasize in Your Cover Letter
['Your technical expertise in multi-modal perception and handling adverse weather conditions, with specific examples from past roles.', 'Your experience leading architectural changes and improving system scalability in a production environment.', "Your passion for autonomous vehicles and alignment with May Mobility's mission of safe, sustainable transportation.", 'Your ability to collaborate with cross-functional teams (e.g., planning, controls) to ensure perception meets system-level requirements.']
Generate Cover Letter →🔍 Research Before Applying
To stand out, make sure you've researched:
- → Read May Mobility's technical blog or papers on their perception stack and safety approach (e.g., their 'fail-operational' strategies).
- → Understand their vehicle platform and sensor suite (cameras, LiDAR, radar) and how they handle sensor degradation.
- → Familiarize yourself with their deployment cities and unique challenges (e.g., snow in Ann Arbor, dense urban areas).
- → Look into their partnerships and funding to gauge company stability and growth trajectory.
💬 Prepare for These Interview Topics
Based on this role, you may be asked about:
⚠️ Common Mistakes to Avoid
- Submitting a generic resume without emphasizing perception robustness or multi-modal models—this role demands specificity.
- Focusing only on research or academic projects without demonstrating production-level code and deployment experience.
- Neglecting to discuss how you handle real-world constraints like sensor noise, latency, or limited compute.
📅 Application Timeline
This position is open until filled. However, we recommend applying as soon as possible as roles at mission-driven organizations tend to fill quickly.
Typical hiring timeline:
Application Review
1-2 weeks
Initial Screening
Phone call or written assessment
Interviews
1-2 rounds, usually virtual
Offer
Congratulations!