Application Guide
How to Apply for Senior ML Engineer
at Lime
🏢 About Lime
Lime is a micromobility leader revolutionizing urban transportation with shared electric scooters and bikes, directly addressing climate change and urban congestion. Their mission-driven focus on sustainability and real-world impact makes them unique, offering engineers the chance to solve complex logistics problems that affect millions of riders globally.
About This Role
This Senior ML Engineer role focuses on optimizing Lime's core operations through demand forecasting and vehicle positioning algorithms, directly impacting rider availability and fleet efficiency. You'll execute multi-year ML strategy at global scale while mentoring engineers, making this a high-impact technical leadership position.
💡 A Day in the Life
A typical day involves analyzing fleet performance data to identify optimization opportunities, collaborating with operations teams on deployment strategies, refining positioning algorithms based on real-world feedback, and mentoring junior engineers on ML best practices. You'll balance hands-on coding with strategic planning for Lime's multi-year ML roadmap.
🚀 Application Tools
🎯 Who Lime Is Looking For
- Has 5+ years building production ML systems with demonstrated experience scaling algorithms (not just prototyping)
- Possesses strong Python skills with PyTorch/TensorFlow experience and can demonstrate SQL/Spark/Pandas proficiency for large-scale mobility data
- Can show specific examples of turning data insights into business value, particularly in logistics, supply chain, or spatial optimization domains
- Has experience mentoring engineers and driving ML strategy, not just individual contributor work
📝 Tips for Applying to Lime
Highlight specific experience with spatial/temporal forecasting models (time series, geospatial ML) rather than generic ML projects
Quantify impact in previous roles using metrics like 'reduced vehicle downtime by X%' or 'improved forecast accuracy by Y%'
Demonstrate understanding of Lime's operational challenges by mentioning specific use cases like rebalancing, demand prediction, or maintenance optimization
Show experience with production ML systems at scale - mention specific technologies and deployment challenges you've overcome
Tailor your resume to emphasize collaboration with operations/product teams, not just technical achievements
✉️ What to Emphasize in Your Cover Letter
["Explain why Lime's sustainability mission resonates with you personally and professionally", 'Describe a specific project where you scaled ML systems in production, emphasizing measurable business impact', 'Highlight experience with spatial data or logistics optimization relevant to scooter/bike positioning', "Mention mentoring experience and how you've raised team ML capabilities"]
Generate Cover Letter →🔍 Research Before Applying
To stand out, make sure you've researched:
- → Study Lime's expansion patterns and operational challenges in different cities (density, regulations, competition)
- → Research micromobility industry trends, especially around rebalancing algorithms and demand prediction
- → Understand Lime's sustainability reports and environmental impact goals
- → Look into Lime's tech blog or engineering talks for insights into their current ML stack and challenges
💬 Prepare for These Interview Topics
Based on this role, you may be asked about:
⚠️ Common Mistakes to Avoid
- Focusing only on academic ML projects without production deployment experience
- Not demonstrating understanding of Lime's specific business model and operational constraints
- Presenting generic ML experience without tailoring to spatial/temporal or logistics problems
📅 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!