Machine Learning Engineer - ETA Team

About the Role

Key Responsibilities

• Build Deep Learning models for next-generation ETA that provide the most accurate, scalable and robust time predictions and enhance the consumer, merchant, and dasher experience.
• Own the modeling life cycle end-to-end, including feature creation, model development and testing, experimentation, monitoring and explainability, and model maintenance.
• Work with data scientists, engineers, and product managers to develop and iterate on models to help grow the business and improve service quality.
• Leverage robust data and machine learning infrastructure to develop inference and optimization ETA models impacting millions of users.
• Explore new opportunities where ETA can be used as a lever for new business, markets, and regions.

Requirements

• 1+ years of industry experience post-PhD or 3+ years of industry experience post-graduate degree in developing advanced machine learning models with business impact.
• M.S., or PhD. in Computer Science, Statistics, or related quantitative fields.
• Strong background in Deep Learning and OSS ML technologies such as Spark, PyTorch, Airflow with hands-on experience in production.
• Demonstrated expertise with programming languages e.g. Python and machine learning libraries e.g., Spark MLLib, PyTorch.
• Deep understanding of complex systems such as Marketplaces, and domain knowledge in two or more of the following: Deep Learning, Reinforcement Learning, Operations Research / Optimization, and LLM.
• Experience shipping production-grade ML models and optimization systems, and designing sophisticated experimentation techniques.
• Location or planned relocation to San Francisco, CA, Sunnyvale, CA, or Seattle, WA.

Nice to Have

• Experience with complex systems such as Marketplaces.
• Knowledge in Reinforcement Learning, Operations Research / Optimization, and LLM.
• Hands-on experience with designing and deploying sophisticated experimentation techniques.

Qualifications

• Educational background with an M.S. or PhD. in Computer Science, Statistics, or related fields.

Benefits & Perks

• Competitive salary within the specified pay ranges, determined by skills, experience, and location.
• Opportunities for equity grants.
• Comprehensive benefits including 401(k) with employer matching, paid parental leave, wellness benefits, commuter benefits, paid time off, and paid sick leave.
• Medical, dental, and vision benefits, 11 paid holidays, disability and life insurance, family-forming assistance, mental health programs.
• Paid time off details vary for salaried and hourly roles, including flexible vacation and sick leave.