About the team
Uber Eats is looking for an experienced and motivated Scientist to join our Content Intelligence Team. In this role, you will significantly contribute to improving the user experience for millions of Uber Eats customers globally. You will apply your knowledge in data analysis, machine learning, and statistical modeling to generate insights and develop new deep-learning algorithms that will enhance our technology framework.
This position offers the chance to innovate our technology stack by utilizing the latest breakthroughs in Deep Learning Research, LLMs, and NLP algorithms to create intricate autonomous systems and recommendation engines throughout the Uber Eats framework.
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About the Role
- Conduct thorough analyses of large datasets to identify trends, patterns, and opportunities for improving machine learning systems' performance.
- Design, implement, and optimize embedding/deep learning models and algorithms.
- Generate actionable insights from data and communicate findings to stakeholders across the organization.
- Work as a thought expert for your cross-functional partners, pushing the boundaries of the goals for your working group.
- Design experiments and interpret the results to draw detailed and impactful conclusions.
- Work closely with product managers, senior engineers, and other scientists to define project goals and deliver data-driven solutions.
- Stay current with the latest advancements in data science, machine learning, AI, and RecSys/search technologies.
- Define how your cross-functional team measures success by developing metrics in close partnership with cross-functional partners.
Technical Skills
Required
- Senior and/or Staff seniority working as an Applied Scientist, Machine Learning Engineer, or equivalent.
- Experience building machine learning systems in production for large-scale applications.
- Experience training/building Deep Learning, LLMs, and/or NLP models.
- Experience using Python to work with large data sets at scale.
- Experience using SQL in a production environment.
- Experience in experimental design and analysis, exploratory data analysis, and statistical analysis.
- Experience using statistical methodologies such as sampling, statistical estimates, descriptive statistics, or similar.
Please note: this hybrid position is based in São Paulo, Brazil - welcoming both local professionals and those open to relocating to São Paulo.
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.