Uber Machine Learning Engineer 

United States, West Virginia 

58529222

About the Role

To support and facilitate this work, we have also developed our in-house ML and optimization infrastructure, including data ETL, feature store, dev & viz tooling, model training, serving, storage and backtest solutions. We extensively use the latest technologies and libraries, such as HDFS, Spark, Ray, PyTorch, Horovod, Modin, etc, in our systems.

What the Candidate Will Do:

• Design and build Machine Learning models with optimization engines.
• Productionize and deploy these models for real-world application.
• Review code and designs of teammates, providing constructive feedback.
• Collaborate with Product and cross-functional teams to brainstorm new solutions and iterate on the product.

Basic Qualifications:

• Bachelor’s degree or equivalent in Computer Science, Engineering, Mathematics or related field, with 2+ years of full-time engineering experience or PhD new grad
• Experience working with multiple multi-functional teams(product, science, product ops etc).
• Expertise in one or more object-oriented programming languages (e.g. Python, Go, Java, C++).

Preferred Qualifications:

• 1+ year of ML experience and building ML models
• Experience with the design and architecture of ML systems and workflows.
• Experience with building algorithmic solutions in production, making practical tradeoffs among algorithm sophistication, compute complexity, maintainability, and extensibility in production environments.
• Experience with taking on vague business problems, translating them into ML + Optimization formulation, identifying the right features, model structure and optimization constraints, and delivering business impact.
• Experience with optimizing Spark queries for better CPU and memory efficiency.
• Working knowledge of latest ML technologies, and libraries, such as PyTorch, TensorFlow, Ray, etc.
• Experience owning and delivering a technically challenging, multi-quarter project end to end.
• Experience with big-data architecture, ETL frameworks and platforms, such as HDFS, Hive, MapReduce, Spark, , etc.

For San Francisco, CA-based roles: The base salary range for this role is USD$158,000 per year - USD$175,500 per year.

For Sunnyvale, CA-based roles: The base salary range for this role is USD$158,000 per year - USD$175,500 per year.