Engineering Manager II, Rider Personalization

About This Role

Manage the Rider Intelligence team to create an intuitive and personalized app experience for millions of riders using cutting-edge machine learning and AI, ensuring the app anticipates their needs and helps them discover relevant products and services.

Responsibilities

• Define and execute the Rider ML product and engineering roadmap and strategy for personalization and discovery experiences
• Direct the design and deployment of real-time machine learning services and APIs to support diverse platform goals
• Partner effectively with cross-functional teams to gather real-time, high-quality data for content ranking and personalization
• Collaborate with key stakeholders to define Key Results (KRs) and align team execution plans
• Coordinate with technical leads to develop robust on-call protocols, alerting, and monitoring systems for ML models and serving infrastructure
• Stay informed on the latest AI/ML research and industry advancements, evaluating and integrating relevant innovations into production
• Hire, develop, and retain top-tier machine learning professionals while nurturing a culture of innovation and teamwork

Requirements

• MS or equivalent experience in Computer Science, Engineering, Mathematics or related field
• 8+ years of industry experience as an Applied Scientist/Machine Learning Engineer
• 3+ years of experience leading a team as a manager
• Experience in exploratory data analysis, statistical modeling, hypothesis testing, and experimental design
• Experience working with cross-functional teams (product, science, product ops etc)

Qualifications

• MS or equivalent experience in Computer Science, Engineering, Mathematics or related field
• 8+ years of industry experience as an Applied Scientist/Machine Learning Engineer with 3+ years of experience leading a team as a manager.

Nice to Have

• Ph.D. in Computer Science, Machine Learning, or a closely related discipline
• 8+ years of industry experience designing, deploying, and operating large-scale production machine learning systems
• Background in search, recommendation systems, ranking/retrieval, or representation learning
• 3+ years of leadership experience managing engineering teams (TLM or EM) with strong cross-functional collaboration and communication skills
• Practical experience building production-grade recommender systems or ML systems (search, speech/audio, or image recognition)
• Proficiency in deep learning frameworks like PyTorch, Keras, or TensorFlow
• Demonstrated success leading cross-functional initiatives with tight deadlines
• Excellent at communication, alignment-building, and influence across complex organizational structures
• Experience at coaching/mentoring engineers to elevate performance and keep top talent motivated and engaged

Skills

* Required skills

Benefits