What the Candidate Will Do
- Work with machine learning engineers to fine tune and optimize machine learning models.
- Monitor and maintain machine learning models in production, ensuring proper functionality and performance, while addressing any issues or bugs (KTLO - keep the lights on).
- Collaborate with cross-functional teams to identify customer pain points and inefficiencies in mobile products, developing machine learning solutions to address them.
- Work with third-party vendors and open-source communities to incorporate existing solutions, libraries, and tools that can accelerate development or improve the performance of the company's machine learning models.
- Partner with privacy and security teams to protect user data and uphold the integrity of machine learning solutions.
- Responsible for conducting comprehensive code reviews across both iOS and Android platforms to ensure high-quality code and adherence to best practices (note: candidate need only write production code for Android but be able to do reviews on both).
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Basic Qualifications
- Bachelor's or Master's degree in Computer Science, Data Science, or a related field (focus on ML/AI is a plus).
- 3-5 years of experience in executing Android-based projects, providing technical guidance and training in Android development to teams of mobile engineers, and ensuring successful project completion.
- Deep expertise in Java or Kotlin, with a thorough understanding of the Android SDK, architecture components, and design patterns.
- Familiarity with mobile development tools such as Android Studio, and experience with version control systems (e.g., Git).
- Excellent communication skills, with the ability to explain complex technical concepts to non-technical stakeholders and third-party collaborators (e.g., Google, Apple).
Preferred Qualifications
- Experience in implementing and deploying machine learning models on mobile platforms, utilizing frameworks like TensorFlow Lite, MLKit, or PyTorch Mobile.
- Familiarity with ML lifecycle management (e.g., data preprocessing, model training, evaluation, quantization, and deployment), and experience collaborating with data scientists or ML engineers to optimize and integrate models into mobile applications.
- Extensive knowledge of computer vision applications, including image and video processing, object detection, and tracking.
- Solid understanding of machine learning concepts and algorithms, such as neural networks, decision trees, and clustering.
- Experience with low-level programming and APIs, understanding how mobile hardware works, and how to optimize code for performance.
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.