Whether engineering more accurate ETAs or helping drivers navigate to the perfect pick-up spot, our mapping technologies are integral to the...
Whether engineering more accurate ETAs or helping drivers navigate to the perfect pick-up spot, our mapping technologies are integral to the magic of the Uber platform. On the Maps Engineering team, we use the latest ML, GPS, and telematics solutions to make transportation on our platform safer and more accessible.
About the Role
What You'll Do
- Our mission is to provide accurate location search results for every customer with the least friction by understanding their intent and queries.
- Design for high-performance, highly scalable, distributed search applications involving indexing, ranking, query understanding (classification, spell check, tagging etc) and document understanding etc.
- Have a direct influence on the product experience for millions of users every day serving billions of queries per month.
- We own the entire backend stack and ML stack from the nitty gritty details of indexing, ranking, query understanding to the presentation layer of the Rider app. We also power delivery search experience for other products like Eats, Freight and so on.
- Tech stack: Backend services (Java), ML modeling (Python/Spark), Data pipelines (Spark - Java / Scala).
We are a very small team of engineers responsible for determining a convenient origin and destination of all trips worldwide. We own the search platform and backend services that power the pickup and dropoff experiences for all Uber jobs - be it Rides, Eats, or Freight!
As a machine learning engineer on this team you would help us build out the ML models to understand queries and documents. You will be scaling your solutions to the tens of thousands of queries across the globe we receive every second. You'd also contribute to the launch of new product features that directly impact the trip search experience. These features directly impact key business KPIs such as search abandonment and time spent in search which impact the overall bottom line of Uber. You will be responsible for the End to End of the product - ML model pipeline & backend system design, implementation, AB testing, and rollout.
You will be working with some of the world's most experienced mapping professionals, data scientists, software engineers, and research scientists on a very user-facing product. This is your chance to develop cutting-edge technology that will make a huge impact on the efficiency of every Uber trip!Basic Qualifications
- Bachelor's degree in Computer Science or related technical field or equivalent practical experience
- Experience building Machine models at industry scale and ability to use machine learning frameworks
- Experience working on large scale Machine Learning platforms.
- Experience coding with C++, Java, Python, or Go
- At least five (5) years of software engineering experience and building production scale ML models.
- Experience shipping high-quality features on schedule
- Experience building large scale distributed systems
- Experience implementing projects with multiple dependencies
- Experience with Search, Information retrieval, and Ranking
- Detailed problem-solving approach and knowledge of algorithms, data structures, and complexity analysis.
- provided by Dice