Application Guide
How to Apply for Lead Data Scientist (ML)
at May Mobility
🏢 About May Mobility
May Mobility is pioneering autonomous electric vehicles specifically designed for safe, sustainable, and eco-friendly transportation. Unlike many tech companies, they focus on solving real-world urban mobility challenges with a safety-first approach, making them an ideal workplace for those passionate about applying cutting-edge technology to create tangible environmental and societal impact.
About This Role
As Lead Data Scientist (ML) at May Mobility, you'll design, implement, and deploy state-of-the-art machine learning models for autonomous vehicle systems while leading code quality initiatives and mentoring team members. This role is impactful because you'll directly contribute to the safety and reliability of self-driving technology that reduces carbon emissions and transforms urban transportation.
💡 A Day in the Life
A typical day involves collaborating with cross-functional teams to refine ML system requirements, implementing and testing deep learning models for vehicle perception or prediction, conducting code reviews with team members, and preparing visualizations to communicate model performance metrics to both technical and business stakeholders. You'll balance hands-on coding with leadership responsibilities to ensure ML systems meet safety and performance standards.
🚀 Application Tools
🎯 Who May Mobility Is Looking For
- Has 10+ years of hands-on experience specifically in building production-level ML systems with deep learning frameworks like TensorFlow or PyTorch
- Demonstrates expertise in algorithmic design for real-time systems, particularly relevant to autonomous vehicle perception, prediction, or control
- Possesses strong communication skills to explain complex ML concepts to both engineering teams and non-technical stakeholders in the transportation industry
- Has experience leading technical teams through design reviews and quality assurance processes in safety-critical applications
📝 Tips for Applying to May Mobility
Highlight specific experience with deploying ML models in production environments, especially for real-time or safety-critical systems
Showcase projects where you've worked with cross-functional teams (hardware, software, product) since May Mobility emphasizes this collaboration
Demonstrate your understanding of autonomous vehicle challenges by mentioning relevant ML applications like sensor fusion, object detection, or path prediction
Quantify your impact on model performance improvements and deployment efficiency in previous roles
Tailor your resume to emphasize both your technical leadership experience and hands-on ML engineering skills, as this role requires both
✉️ What to Emphasize in Your Cover Letter
['Your experience with deploying production ML systems and how it relates to autonomous vehicle technology', 'Specific examples of leading technical teams through design/code reviews in safety-critical domains', 'Your ability to communicate complex ML concepts to diverse stakeholders (engineers, product managers, possibly regulators)', "Why you're passionate about applying ML to sustainable transportation and autonomous vehicles specifically"]
Generate Cover Letter →🔍 Research Before Applying
To stand out, make sure you've researched:
- → May Mobility's specific autonomous vehicle technology stack and deployment cities
- → Their safety philosophy and how ML integrates into their overall system architecture
- → Recent news about their partnerships, funding rounds, or technological milestones
- → The specific challenges of autonomous shuttles in urban environments versus other autonomous vehicle applications
💬 Prepare for These Interview Topics
Based on this role, you may be asked about:
⚠️ Common Mistakes to Avoid
- Focusing only on academic ML research without demonstrating production deployment experience
- Using generic ML examples instead of discussing applications relevant to autonomous vehicles or real-time systems
- Failing to show leadership experience or examples of mentoring/guiding technical teams
📅 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!