Senior Software Engineer - ML

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