About the Company
Uber is a global technology platform redefining how people move, earn, and access goods. From its beginnings in 2008 as a simple ride-hailing app, Uber has evolved into a worldwide network powering flexible earnings and the real-time movement of people, meals, freight, and essential items. Operating in cities around the globe, Uber continually reimagines mobility, delivery, and logistics—always with a commitment to innovation, safety, and reliability.
About the Role
This position is part of the Basemaps team in Uber’s Amsterdam tech hub, focusing on developing the next generation of map technology. The Senior Machine Learning Engineer will design, build, and deploy scalable ML systems for computer vision and geospatial image processing. The work will drive improvements in road network accuracy, hazard detection, and platform safety, impacting millions of users worldwide.
Responsibilities
- Design and implement ML models for computer vision and geospatial image analysis.
- Translate operational requirements into scalable technical solutions and define success metrics.
- Lead the development of end-to-end ML pipelines, including data processing, model training, deployment, testing, and rollout.
- Create systems that detect, resolve, and enhance map data quality.
- Identify new road features and expand geographic coverage using imagery and other data sources.
- Collaborate cross-functionally with product, data science, engineering, and operations teams to deliver robust solutions.
Required Skills
- PhD or equivalent in Computer Science, Engineering, Mathematics, or related discipline.
- Minimum 5 years of industry software engineering experience, including at least 3 years in computer vision.
- Strong expertise in supervised learning, deep learning (CNNs), and probabilistic modeling.
- Hands-on experience with TensorFlow, PyTorch, OpenCV, and Scikit-Learn.
- Proficiency in Python, Go, or Java.
- Experience with large-scale data processing tools such as MapReduce, Spark, and Hive.
- Solid knowledge of algorithms, data structures, and computer architecture.
Preferred Qualifications
- Experience with geospatial data and vision-based mapping solutions.
- Background in building distributed systems at scale.
- Familiarity with satellite imagery, street-level imagery, LiDAR, or similar sensor data.
- Proven track record in production software deployment and monitoring.
- Ability to convert technical insights into actionable business strategies.
- Willingness to participate in on-call rotations for high-availability systems.