Uber's Marketplace Engineering team creates the technology behind our ridesharing marketplace by connecting riders with drivers at the push of a button. Our solutions expand user access, deliver reliability, and provide more transportation choices to users across our global markets.
About the Role
Uber Marketplace ( ) is at the core of Uber's business, and Fares is a strategically important component of Marketplace. The mission of the team is to achieve long term sustainable growth, increase User engagement and increase profitability of Uber by pushing the frontiers of machine learning, and developing highly reliable and scalable platforms to accelerate Uber's impact to the transportation industry. The team is in its formation phase with many new areas to venture into, is rapidly growing with high impact it can achieve and has visibility from the top. We are responsible for developing state of the art technology to influence Fares strategy in our platform that directly drives efficiencies and effectiveness across all user interactions with Uber. We aim to build long-term engagement among Uber users and create a healthy and balanced ecosystem. It is a challenging yet rewarding job.
You will participate the whole development cycle of a software product from ideation, scoping, architecture design, implementation, to productionization, and learn how to iterate on a product for making greater impact. We own a few key products that directly impact Uber's bottom line. We are a data driven team, and you will be able to see the impact of your work reflected in Uber's earning report, such as gross booking, trips and number of active users.
What You'll Do
• Lead Machine learning efforts across Marketplace Fares
• Solve open ended business and/or technical problems to drive engagement & derive long term growth in a fast paced environment
• Work with Product, Data Science and several engineering teams to add new features and scale the platform
• Lead and mentor other engineers on the team
• 7+ years of software engineering experience with PhD in relevant fields (EE, CS, Stats, Math, etc), or equivalent experience
• 3+ years of Machine Learning and Data mining experience (training, building & productionizing models)
• Engineering experience in hands-on software development with thoughtfulness of scale, latency and distributed architecture
• Highly efficient coding in Java, Golang or any similar languages.
• Knowledge of data-driven architecture and systems design
• Some experience in leading teams either as a tech lead or a manager
• Experience with converting business problems into ML problems
• Experience with causal learning and/or deep learning
• Experience working with large dataset storage systems like NoSQL, HDFS (+Hive) and data distribution systems like Kafka
• A willingness and curiosity to learn both the systems and domain in which you will be solving problem statements
• A great teammate and owner- willing to take on ownership of the systems, and think about operations, maintenance and reliability of his/her systems
• Proven experience of shipping high-quality product features on schedule.
At Uber, we ignite opportunity by setting the world in motion. We take on big problems to help drivers, riders, delivery partners, and eaters get moving in more than 10,000 cities around the world.
We welcome people from all backgrounds who seek the opportunity to help build a future where everyone and everything can move independently. If you have the curiosity, passion, and collaborative spirit, work with us, and let's move the world forward, together.
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](https://forms.gle/aDWTk9k6xtMU25Y5A).