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Machine Learning Engineer (Sensor Intelligence)






San Francisco, CA, US


At Uber, we ignite opportunity by setting the world in motion. We take on big problems to help drivers, riders, delivery partners, and eaters get moving in more than 600 cities around the world.


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.

About the Role

As a Machine Learning engineer on the team, you will be working with a wide range of sensor data (location, motion, camera, etc) to develop inferences that enable some of the most important parts of Uber’s business - Fares, Matching, Safety, Pickup Experience, and more. Our systems stream more than 6 TB of data a day, producing inferences like Crash Detection and Trip State Model, that improve the Uber experience for both riders and drivers.

What You’ll Do

  • Explore our massive dataset of sensor data from GPS, IMU, barometer, etc to discover opportunities to improve Uber’s product.  
  • Research and develop machine learning models (crash detection, phone handling, harsh braking, trip states) that provide insight about trips and customer experiences.
  • Work with backend infrastructure engineers to architect and build the pipelines to train and serve the machine learning models at Uber scale.
  • Work closely with PMs and engineers on partner teams to integrate and validate systems end to end.  


What You'll Need

  • Masters in CS, EE or related disciplines. PhD preferred.
  • 2+ years of relevant industry / academic experience.
  • Deep knowledge of machine learning algorithms
  • Experience with ML infrastructure and running models at scale in production.
  • Strong programming skills (we mainly use Java & Python)
  • Ability to communicate complex black-box models to cross-functional stakeholders
  • Collaborative attitude and interest in working in a cross-functional team
  • Ability to learn fast and work with ambiguous problem definitions


Bonus Point if

  • You have experience working with sensor or other time-series data (audiovisual, barometric, etc)
  • You have experience  in stream processing—Storm, Spark, Flink etc.


About the Team

Uber is deeply rooted in the physical world -- our business requires a clear understanding of complicated real-world interactions and behaviors.  The Sensing and Perception team seeks to understand these interactions about every trip through the use of sensors.

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