About the Role
At Uber, we're redefining the way the world moves. We connect people with safe, reliable, and affordable transportation across the globe. Our mission is to ignite opportunity by setting the world in motion, and we're just getting started. With a passion for innovation and a commitment to pushing the boundaries of technology, we are constantly striving to improve our services and delight our customers.
Rider personalization is crucial to ensuring that every interaction with the Uber platform feels relevant and responsive to individual user needs. It involves understanding each rider's journey-anticipating their needs before they even articulate them, and delivering experiences that feel uniquely crafted just for them.
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In this role, you will drive the development of sophisticated machine learning models that harness vast amounts of data to make real-time predictions and decisions, significantly improving rider satisfaction and engagement. Your work will directly impact how riders discover and interact with Uber services, making their journey smoother and more personalized.
Staff ML engineers at Uber are passionate and pragmatic technologists who are able to translate business insight and goals into well-formulated ML projects and scalable solutions to deliver impact. They are not only collaborative role models but also approachable leaders, humble teachers while also effective in helping the team in project execution. You will work with talented people in product, science, operations, and platform teams to help build and optimize our Rider Experience products. The role requires technical chops as well as strong communication & leadership skills.
What the Candidate Will Need / Bonus Points
---- What the Candidate Will Do ----
- Defining and driving ML solutions for key strategic problems in the space of product recommendations and merchandising: help riders find and complete rides with the right products, trying to understand their intent and context while attending to Uber's business goals, marketplace conditions and efficiencies.
- Raise the bar of ML engineering by improving best practices, producing exemplary code, documentation, automated tests and thorough and precise monitoring.
- Provide technical leadership to a passionate, experienced, and diverse engineering team. Manage project priorities, deadlines and deliverables and design, develop, test, deploy and maintain ML solutions.
- Partner with product owners, data scientists and business teams to translate key insights and business opportunities into technical solutions
---- Basic Qualifications ----
- achelor's degree in Computer Science, Engineering, Mathematics or related field
- Strong problem-solving skills, with expertise in ML methodologies
- Experience in applying ML, statistics, or optimization techniques to solve large-scale real-world problems (e.g. ads tech, recommender systems)
- Industry experience in ML frameworks (e.g. Tensorflow, Pytorch, or JAX) and complex data pipelines; programming languages such as Python, Spark SQL, Presto, Go, Java
---- Preferred Qualifications ----
- 6+ years of experience in software engineering with an emphasis on data-driven methodologies and online experimentation
- Experience in designing and crafting scalable, reliable, maintainable and reusable ML solutions using deep-learning techniques and statistical methods.
- Innate truth-seeker who values and produces analytic evidence and insight, as well as translating them and business goals into technical problems and solutions.
- 2+ years of experience working in a cross-functional and/or cross-business projects, partnering with Product, Scientists, and cross-org leads to shape the team's strategies
- Passionate about helping junior members grow by inspiring and mentoring engineers
- Resilience, determination, ownership mindset
- PhD degree in Computer Science, Engineering, Mathematics or related field
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.
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.
*Accommodations may be available based on religious and/or medical conditions, or as required by applicable law. To request an accommodation, please reach out to accommodations@uber.com.