Staff Machine Learning Engineer - Pricing & Incentives

About the Role

Key Responsibilities

• Work with product, data science, and engineering leadership to shape the technical roadmap and problem formulations for the team.
• Leverage algorithmic knowledge in machine learning, optimization, and statistics to design robust engineering solutions to positively impact Uber's business.
• Shape the Machine Learning Engineer role and uplevel MLE talents in the organization.
• Be responsible for the end-to-end product - ML model pipeline and system design, implementation, A/B testing, and rollout.
• Work with the team to productionize solutions at scale.

Requirements

• PhD or equivalent in Computer Science, Engineering, Mathematics or related field.
• 4+ years of full-time Machine Learning Engineering work experience in leveraging machine learning, statistics, or optimization to build models in production.
• Collaborative and able to work well with, and contribute to, a team.

Nice to Have

• Experience building algorithms with large scale data.
• Track record of building large-scale, highly-available systems for both batch and streaming.
• Deep domain expertise and recognition as a specialist in areas like reinforcement learning, personalization, or deep learning.
• Experience in combining observational data with experimental data for building causal models.
• Experience working on large scale Machine Learning platforms.

Qualifications

• Educational background with a PhD or equivalent in relevant fields.

Benefits & Perks

• For San Francisco, CA-based roles: The base salary range is USD$223,000 to USD$248,000 per year.
• For Sunnyvale, CA-based roles: The base salary range is USD$223,000 to USD$248,000 per year.
• Eligibility to participate in Uber's bonus program, and potential equity awards and other compensation.
• Various benefits as detailed at https://www.uber.com/careers/benefits.