Senior Machine Learning Engineer - Maps

About the role

Uber’s Maps Places team stitches together noisy signals from dozens of data providers to keep our global points-of-interest map fresh and correct. You will:

• Match the same real-world place even when names, addresses, or coordinates conflict.
• Improve each place’s location, category, and attributes with trip, imagery, and feed data.
• Spot and publish brand-new venues so riders and drivers can find them on day one.

Your models will power every Uber product that depends on knowing exactly where something is and what it is.

What you will do

• Turn coverage, precision, and freshness targets into concrete ML problems.
• Own the full stack: data pipelines, model training, evaluation, A/B tests, rollout, and monitoring.
• Design inference services that scale to millions of daily place updates.
• Partner with backend, data, product, and operations teams to ship end-to-end features.
• Mentor engineers and help shape the ML charter for Maps Places Amsterdam.

Basic qualifications

• PhD or equivalent in CS, Engineering, Math, or related field and 5+ years of software engineering experience, including 3+ years focused on ML.
• Strong grasp of algorithms, data structures, and computer architecture.
• Hands-on with TensorFlow, PyTorch, Spark MLLib, or Scikit-learn.
• Proficient in Python, Java, or Go.
• Experience with large-scale data processing (Spark, Hive, MapReduce).
• Clear communicator who collaborates well across functions.

Preferred qualifications

• Built or operated large-scale distributed systems.
• Experience with geospatial data and place matching.
• Track record of taking ML models from idea to reliable production service used by millions.
• Comfortable participating in an on-call rotation for high-traffic services.
• Able to turn model insights into product and business recommendations.

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.