We’re looking for PhD candidates to intern with the Trusted Identity team during summer 2025 (12 weeks). You will be embedded in an engineering team and collaborate closely with experts in other functions, including data scientists, product managers, etc. As a PhD intern, you will work on an exciting and bold problem in depth independently, under the supervision of an experienced engineer on that team. **About the Role** At Uber, we work on many ambitious engineering products covering many lines of business as well as the underlying platform technologies that power those businesses. We foster growth and increase profitability of Uber by pushing the frontiers of machine learning, constrained optimization, statistics, data science and economics and developing highly reliable and scalable platforms to accelerate Uber’s impact on the transportation industry. As a PhD software engineer intern, you will work on cutting-edge machine learning problems, contribute to research projects, and help develop innovative solutions. This is an excellent opportunity for a PhD candidate looking to bridge academic research with practical applications in industry. You will have an opportunity to learn how to iterate over a product for greater success while demonstrating your area of expertise (machine learning, statistics, constrained optimization, distributed system, etc.). This is a unique opportunity to grow your skills with real-world experience and do highly impactful, yet fun work at the same time. **About the Team** The Trusted Identity org inspires trust in the Uber business cycle through verified and authentic identities. The Account Integrity team prevents fake identities from operating on the platform, and ensures that accounts are not duplicated nor fraudulent to enhance accountability. The Identity Verification team ensures accounts are created by real humans by verifying their attributes. The Account Security team is responsible for defending account holders from fraud related to phishing and ATO (account takeover) attempts. The Device Intelligence team is responsible for collecting device signals that are critical for the other teams to reliably achieve their goals. **What You’ll Do** - **Research & Development:** - Conduct literature reviews to stay current with the latest advancements in machine learning, deep learning, and related areas - Develop, test, and refine novel machine learning models and algorithms tailored to specific project challenges - Explore and implement state-of-the-art techniques to improve model accuracy, scalability, and efficiency - **Implementation & Experimentation:** - Design and build prototypes or proof-of-concept implementations to validate new approaches - Develop scalable and well-documented code using Python (or other relevant languages) and machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-Learn) - Perform extensive experiments, including hyperparameter tuning, model evaluation, and performance benchmarking - **Data Analysis & Problem Solving:** - Collaborate with data engineering teams to understand data characteristics, perform preprocessing, and manage datasets - Analyze experimental results, identify trends, and provide actionable insights to refine research approaches - Troubleshoot issues that arise during model development and deployment - **Collaboration & Communication:** - Work closely with a multidisciplinary team that may include data scientists, software engineers, and domain experts - Document research methodologies, experimental designs, and outcomes in detailed reports - Present findings and progress updates to team members and stakeholders through meetings, presentations, or technical demos - Contribute to writing research papers or technical reports that may lead to publications or patents **Basic Qualifications** - Currently enrolled in a Ph.D. program studying machine learning, data mining, artificial intelligence, constrained optimization, statistics, or a related quantitative field - Candidates should have at least one semester/quarter left of their education after finishing the internship - Knowledge of underlying technical foundations of statistics, machine learning, optimization, and systems, etc. - Experience in one or more object-oriented languages, including C++, Java, Python, or Go - Familiarity with software development best practices, version control systems (e.g., Git), and collaborative coding **Preferred Qualifications** - Proficiency in programming with Python and familiarity with machine learning libraries/frameworks (e.g., TensorFlow, PyTorch, Scikit-Learn) - Experience with data manipulation and visualization tools - Experience with publishing research (conference papers, journals) - Experience with working across both technical and business partners - Experience with productionizing models in an industry setting serving large scale traffic For New York, NY-based roles: The base hourly rate amount for this role is USD$67.00 per hour. For Sunnyvale, CA-based roles: The base hourly rate amount for this role is USD$67.00 per hour. For all US locations, you will also be eligible for various benefits. 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). 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.