About The RoleAre you a technology enthusiast? Does working on Machine Learning (ML) products excite you? Are you thrilled about building the future of the ML ecosystem at Uber? If yes, read on!At Uber, ML has been widely used across all products to directly improve the end user experience. We use ML to predict ETA (Estimated Time of Arrival) for rides and ETD (Estimated Time of Delivery) for UberEats orders. We also use ML to match riders with drivers, recommend restaurants and dishes for eaters, detect fraudulent transactions, automate customer support, and many more things.Our AI Platform team built Michelangelo, one of the industry’s first end-to-end ML platforms, from the ground up. Michelangelo provides industry-leading tools and services for Uber’s ML engineers and data scientists to train, tune, serve, monitor, and debug ML models at scale. Today, all Uber’s business-critical ML applications and use cases are managed and served on Michelangelo.To meet the rapidly changing ML needs and better serve our continuously growing ML community at Uber, we are seeking an experienced and passionate Product Manager. We are looking for a PM with strong technical depth, product intuition and entrepreneurial spirit to lead development and execution of the vision, strategy and roadmap for key components of Michelangelo while ultimately bringing the platform to the next level. What You Will Do

• Work closely with Uber’s Machine Learning engineers, applied scientists, data scientists, and software engineers to thoroughly understand the ML use cases at Uber, identify users’ struggles and opportunities, and gather requirements.
• Set qualitative objectives and quantitative goals, define product requirements, and drive execution with the AI Platform Engineering, TPM, and UX design teams.
• Monitor and measure launched products and feed insights back into the product development process to drive growth.
• Clearly communicate product plans, progress, and results to a spectrum of audiences, from internal stakeholders to customer teams, Uber executives, and external ML communities.

Basic Qualifications

• 5+ years of Product Management experience delivering highly successful data, ML, or platform products.
• A computer science or other engineering degree equivalent.
• Ability to thrive in cross-functional environments and work backward from the needs of your customers to build solutions that scale.
• Data-driven decision-making ability and a "driver" personality for pushing toward clarity and balancing the need for great collaboration.
• High attention to detail and proven track record to multi-task and manage competing priorities.
• Very strong communication skills, both written and verbal.
• A passion for Uber's mission and technology-driven culture, along with a deep desire to grow and learn!

Preferred Qualifications

• Experience building large-scale AI/ML infra or platform products
• Super strong technical background, preferably in AI/ML space. We don’t expect you to code, but you should feel comfortable discussing deep technical topics with engineering teams and the platform users.
• Excellent understanding of MLOps industry trends and best practices
• Experience working with ML/Data platforms such as AWS Sagemaker, GCP Vertex AI, and Databricks.

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.