Senior Staff Machine Learning Engineer - Marketplace Matching & Driver Pricing

$252,000 - $280,000/Yr

Uber - San Francisco, CA

Full-time - Senior

Remote - San Francisco, CA

Transit and Ground Passenger Transportation

About the position

This is a key role as a thought leader and key contributor to Machine Learning efforts across several key domains in Marketplace, specifically focusing on the Job-Driver Matching system, Driver offer pricing, and Driver Surge pricing. The ML models utilized in these domains encompass a variety of approaches, including causal ML models, reinforcement learning models, and forecast models. The challenges faced in these areas include data sparsity and the delay in realizing the impact of actions due to the physical nature of Uber's business. Additionally, network effects arise from the limited supply of drivers shared across riders, long-term behavioral changes within the driver community, and geographical differences in driver values and Uber's business operations. These factors contribute to a complex and open problem space within the field of machine learning, making the impact of this role extremely significant given the marketplace levers it supports. The team is composed of the Driver offer pricing, Matching, and Driver surge teams within the Uber Marketplace organization. This team is responsible for systems that make optimal decisions regarding driver pricing and job-driver matching. They work cross-functionally with various organizations at Uber, including the Earner and Rider teams, Operations, and Platforms, to ensure effective collaboration and decision-making across the board.

Responsibilities

• Contribute to the development and optimization of Machine Learning models for Job-Driver Matching, Driver offer pricing, and Driver Surge pricing.
• Address challenges related to data sparsity and the impact of actions in a physical business environment.
• Collaborate with cross-functional teams to enhance decision-making systems for driver pricing and job-driver matching.
• Utilize modern machine learning algorithms and software to implement scalable ML architecture.
• Engage in research and development of advanced ML techniques, including causal ML and reinforcement learning.

Requirements

• PhD or equivalent in Computer Science, Engineering, Mathematics, or a related field AND 6 years of full-time Software Engineering work experience OR 10 years of full-time Software Engineering work experience.
• 6 years of total technical software engineering experience in programming languages such as C, C++, Java, Python, or Go.
• Experience in large-scale training using data structures and algorithms.
• Proficiency in modern machine learning algorithms, including tree-based techniques, supervised learning, deep learning, or probabilistic learning.
• Familiarity with Machine Learning software such as Tensorflow, Pytorch, Caffe, Scikit-Learn, or Spark MLLib.

Nice-to-haves

• Experience with causal ML techniques.
• Knowledge of reinforcement learning and contextual bandit models.
• Experience in personalization and ranking systems.

Benefits

• Participation in Uber's bonus program.
• Eligibility for equity awards and other types of compensation.
• Various health and wellness benefits as detailed on Uber's careers benefits page.