Staff Machine Learning Engineer
ABOUT THE TEAM
The Earner Incentive team at Marketplace builds ML solutions for incentives to improve marketplace balance and efficiency. The team builds machine learning systems to solve critical ML problems in Marketplace such as forecasting undersupply geo and times, optimizing incentive levers to influence marketplace dynamics, and understanding earner behaviors and preferences for targeting / personalization.
What you'll do:
\* Lead the design, development, optimization, and productization of machine learning (ML) solutions and systems that are used to solve strategically important or vaguely defined problems.
\* Build ML solutions to improve Uber's earner incentive products and improve marketplace balance and efficiency.
\* Lead ML engineers, provide technical leadership and directions for the team.
Basic Qualifications:
\* PhD or equivalent experience in Computer Science, Engineering, Mathematics or a related field and 5 years of Software Engineering work experience.
\* Experience in programming with a language such as Python, C, C++, Java, or Go.\
\* Experience with ML packages such as Tensorflow, PyTorch, JAX, and Scikit-Learn.
\* Experience with SQL and database systems such as Hive, Kafka, and Cassandra.
\* Experience in the development, training, productionization and monitoring of ML solutions at scale.
Preferred Qualifications:
\* Experience in a technical leadership role.
\* Experience in modern deep learning architectures and probabilistic models.
\* Experience in optimization (RL / Bayes / Bandits) and online learning.
For San Francisco, CA-based roles: The base salary range for this role is USD$218,000 per year - USD$242,000 per year.
For Sunnyvale, CA-based roles: The base salary range for this role is USD$218,000 per year - USD$242,000 per year.
For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. You will also be eligible for various benefits. More details can be found at the following link https://www.uber.com/careers/benefits.
Uber is proud to be an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing this form.
Offices continue to be central to collaboration and Uber’s cultural identity. Unless formally approved to work fully remotely, Uber expects employees to spend at least half of their work time in their assigned office. For certain roles, such as those based at green-light hubs, employees are expected to be in-office for 100% of their time. Please speak with your recruiter to better understand in-office expectations for this role.
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