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Home›Jobs›Uber›Staff Machine Learning Engineer - Pricing & Incentives
Uber

About Uber

Reimagining transportation for a better world

🏢 Tech👥 1001+ employees📅 Founded 2009📍 Mission Bay, San Francisco, CA💰 $15.8b⭐ 3.9
B2CTravelMarketplaceTransportRidesharingDelivery

Key Highlights

  • Public company (NYSE: UBER) since May 2019
  • Completed over 1.5 billion trips globally
  • Generated $4.8B in revenue from Uber Eats in 2020
  • Raised $15.8 billion in funding

Uber Technologies, Inc. (NYSE: UBER) is a leading ride-hailing platform headquartered in Mission Bay, San Francisco, CA. Founded in 2009, Uber has transformed transportation services, completing over 1.5 billion trips globally. The company went public in May 2019 and has raised $15.8 billion in fund...

🎁 Benefits

Uber provides comprehensive healthcare, a robust employee stock purchase plan, generous paid vacation, and a four-week sabbatical after five years of ...

🌟 Culture

Uber fosters a culture of innovation and adaptability, continuously expanding its services beyond traditional ride-hailing. The company emphasizes wor...

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Uber

Staff Machine Learning Engineer - Pricing & Incentives

Uber • San Francisco, USA

Posted 5 months ago🏛️ On-SiteLeadMachine learning engineer📍 San francisco
Apply Now →

Job Description

**About the Role** The role will be within the pricing and incentives domain in Uber's marketplace team. The team charter spans incentive allocation and optimization to balance the market and optimize revenue, dynamic trip pricing based on marketplace conditions. The role will provide an opportunity to work on some of the most strategic marketplace problems at Uber scale that impact Uber's global business very directly. **What You Will Do:** - Work with product, data science, and eng leadership to shape the technical roadmap and problem formulations for the team. - Leverage algorithmic knowledge in machine learning/optimization/statistics to design robust engineering solutions to positively impact Uber's business. - Shape the MLE role and uplevel MLE talents in the org. - Be responsible for the End to End of the product - ML model pipeline & system design, implementation, AB testing, and rollout. Work with the team to productionize the solutions at scale. **Basic Qualifications:** - PhD or equivalent in Computer Science, Engineering, Mathematics or related field - 4+ years full-time Machine Learning Engineering work experience in leveraging machine learning/statistics/optimization to build models in production - Collaborative and work well with, and contribute to, a team **Preferred Qualifications:** - 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 are one of the recognized specialists in one or multiple 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 For San Francisco, CA-based roles: The base salary range for this role is USD$223,000 per year - USD$248,000 per year. For Sunnyvale, CA-based roles: The base salary range for this role is USD$223,000 per year - USD$248,000 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](https://www.uber.com/careers/benefits). Uber's mission is to reimagine the way the world moves for the better. Here, bold ideas create real-world impact, challenges drive growth, and speed fuels progress. What moves us, moves the world - let's move it forward, together. Uber is proud to be an Equal Opportunity 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](https://forms.gle/aDWTk9k6xtMU25Y5A). 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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