About The Role
Uber is changing the way people think about transportation. Not that long ago, we were just an app to request premium black cars in a few metropolitan areas. Now we're a part of the logistical fabric of cities everywhere. Whether it's a ride, a sandwich, or a package, we use technology to give people what they want, when they want it.
About The Team
Uber is hiring a Staff Machine Learning Engineer to join the Basemaps team in our Amsterdam tech office to help deliver top-tier map offerings that power our entire business. There is a unique opportunity to lead the effort of map curation and enrichment via inference and models that will help introduce new road network features, improve precision, and find map issues that reduce efficiency or expose road hazards.
What The Candidate Will Do
- Translate business level metrics to an engineering/science problem.
- Shape the MLE role for the Maps AMS team.
- Be responsible for the End to End of the product - ML model pipeline & backend system design, implementation, AB testing, and rollout.
- Build new services that aim to significantly increase map issue resolution rate and accuracy, curate map features, and improve overall coverage.
- Collaborate in a team environment across all functions, including but not limited to engineers, product managers, data scientists, and operations.
Basic Qualifications
- PhD or equivalent in Computer Science, Engineering, Mathematics or related field AND 8-years full-time Software Engineering work experience, WHICH INCLUDES 5-years total technical software engineering experience in one or more of the following areas:
- Training using data structures and algorithms.
- Modern machine learning algorithms (e.g., tree-based techniques, supervised, deep, or probabilistic learning).
- Machine Learning Software such as Tensorflow/Pytorch, Caffe, Scikit-Learn, or Spark MLLib.
- Sound understanding of computer architecture and CS fundamentals.
- Proficient in one of the following programming languages: Java, Go, Python.
- Experience with MapReduce, Spark, and Hive on large datasets.
- Collaborative and work well with, and contribute to, a team.
Preferred Qualifications
- Experience working on large-scale distributed systems.
- Experience working on large scale Machine Learning platforms.
- Engineering work, internships, relevant course-work, or project experience in any of the following areas: machine learning, search, ranking, recommendation systems, pattern recognition, data mining, or artificial intelligence.
- Proven experience developing sophisticated software systems scaling to millions of users with production quality deployment, monitoring, and reliability.
- Proven track record to translate insight into business recommendations.
- Experience participating in on-call rotation for high scale distributed system domain.
Benefits Extracted with AI
- Flexible work environment
- Opportunities for professional growth
- Collaborative team environment
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