Senior ML Engineer

Job not on LinkedIn

September 29

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Lime

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Transport • eCommerce • SaaS

Lime is a transportation company that provides shared electric scooters and bikes in urban areas, making it easy for users to travel short distances. With a focus on safety, sustainability, and community, Lime aims to offer an eco-friendly alternative to traditional transportation methods. Users can easily locate and rent vehicles through the Lime app, promoting responsible riding and parking practices to enhance the urban mobility experience.

501 - 1000 employees

Founded 2017

🚗 Transport

🛍️ eCommerce

☁️ SaaS

💰 $418M Convertible Note on 2021-11

📋 Description

• Build and improve Lime’s demand forecasting and vehicle positioning algorithms to ensure riders have access to a scooter or bike when and where they need it • Drive execution of Lime’s multi-year ML strategy, applying state-of-the-art technologies, processes, and techniques to production systems at global scale • Collaborate with product managers, data scientists, engineers, and operations leaders to make high-impact technical and product decisions • Mentor and coach engineers, raising the bar on ML expertise and engineering excellence across the team • Design, build, and scale ML systems that power deployment and rebalancing decisions for Lime’s shared electric vehicles

🎯 Requirements

• 5+ years of professional software engineering and ML experience • Strong coding skills in Python • Experience with modern ML frameworks (e.g., PyTorch, TensorFlow) • Experience with data tools (SQL, Spark, Pandas) • Skilled at turning data exploration and insights into business-impacting projects • Experience taking ML models from prototype to production, including deployment, monitoring, and iteration • Strong collaborator; experience partnering with product, operations, and engineering teams • Passionate about mentoring and raising technical bar • Expertise in time-series modeling and demand forecasting at scale (preferred) • Background in optimization or operations research, particularly applied to logistics, scheduling, or large-scale planning problems (preferred) • Familiarity with A/B testing, causal inference, or other experimentation methods (preferred) • Experience with geospatial or spatiotemporal data in applied ML (preferred)

🏖️ Benefits

• Annual performance bonus • Equity (stock/equity may be provided) • Benefits (unspecified, part of compensation package) • Offers Equity • Offers Bonus