What the Candidate Will Need:
- Technical Leadership: Demonstrated ability to lead and manage high-performing engineering teams, particularly in the ML and AI domain.
- Hands-on Engineering Background: A strong foundation in software engineering, with a track record of building and deploying robust, scalable systems.
- ML and AI Expertise: Proficiency with machine learning frameworks such as TensorFlow, PyTorch, or similar, and a deep understanding of the ML lifecycle.
- Cross-functional Collaboration: Proven ability to work cross-functionally, effectively communicating and advocating for the team across different departments.
- Roadmap Execution: A solid history of executing complex roadmaps, delivering projects on time, and maintaining high-quality standards.
Want more jobs like this?
Get Data and Analytics jobs in Amsterdam, Netherlands delivered to your inbox every week.
Bonus Points:
- Advanced ML/AI Experience: Experience with advanced ML/AI techniques, such as deep learning or reinforcement learning.
- Experience with High-Performance Computing: Expertise in optimizing computing resources for ML workloads, including experience with GPU/TPU and other specialized hardware.
- Open Source Contributions: Active involvement in the ML or software engineering community through open source contributions.
- Data Science Dependency Management: Experience in managing dependencies in complex data science projects.
- Problem-Solving Prowess: A systematic approach to solving complex technical problems, with a deep understanding of algorithms and data structures.
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.