About the Role

As an ML Engineer, you should be able to apply Machine Learning to Solve complex business problems and optimize customer experience, and work closely with stakeholders to formulate machine learning problems within the business context.

Build end-end ML systems for designing, training, testing, optimization, deploying, and serving machine learning models. Write ML system design docs and production-level codes to train your ML models into working pipelines and serve models for large-scale online traffic.

About the team

The Data Intelligence Platform team is responsible for designing core foundational data sets critical to understanding customers' needs and helping business teams make the right decisions in solving these crucial problems. The team’s mission is to ensure high quality for all the critical data flows for analytics purposes across all verticals in Uber and enable faster implementation of data needs by building standardized tools and frameworks for accurate analysis. We are now expanding our charter to solve some of the critical business problems using ML Engineering for the Mobility Business.

Join us to be part of a thriving culture while solving exciting problems at scale.

Basic Qualifications

1\. Engineering Degree or equivalent in Computer Science, related field

2\. Experience in one or more Programming languages (e.g. C, C++, Java, Python, or Go)

3\. Training using data structures and algorithms

4\. Modern machine learning algorithms (e.g., tree-based techniques, supervised, deep, or probabilistic learning)

5\. Machine Learning Software such as Tensorflow/Pytorch, Caffe, Scikit-Learn, or Spark MLLib

6\. Good problem-solving and analytical skills

7\. Good team player and collaboration skills.

Preferred Qualifications

1\. 7+ years of professional software engineering experience in industry

2\. Experience deconstructing real problems, including selecting the proper data structure and developing an appropriate algorithm and pushing to production

3\. Experience designing ML solutions, and implementing those solutions at scale

4\. Scalable ML architecture

5\. Deep Learning experience

What the Candidate Will Do

Build ML solutions to solve business needs across the Rider organization with over 300+ engineers. Some of the types of projects you will work on for e.g:

1\. Address the under-supply problem and reduce the pickup ETA

2\. Improve the overall experience of the Riders at the Airport

Uber's mission is to reimagine the way the world moves for the better. Here, bold ideas create real-world impact, challenges drive growth, and speed fuelds progress. What moves us, moves the world - let’s move it 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](mailto:accommodations@uber.com).