Uber Staff Machine Learning Engineer - Delivery Marketplace 

United States, West Virginia 

342950692

About the Role

Staff MLEs lead efforts within the team and broader Delivery Marketplace organization to drive ideation, development and productionization of optimization solutions with real-time and ML model-based signals that solve strategically important problems. Some existing problem spaces that the team works on:

• Using statistical/machine learning/forecasting models for demand and supply models
• State of the art prediction models for estimating food preparation times, batching quality as well as time spent by couriers at restaurants picking up items.
• Develop objective function which balances magical user experience and economics of the business

It is a challenging yet rewarding job. You will have a lot of opportunities to work with product managers, data scientists and engineers from other teams. You will guide/mentor a group of MLEs in the end-to-end development cycle from product ideation, model development and productionization at scale. You will be in-charge of solving Uber scale problems with the right techniques like reinforcement learning/deep learning/optimization methods.

What You Will Do

• Lead the design, development, optimization, and productization of machine learning (ML) solutions and systems that are used to solve strategically important or vaguely defined problems.
• Build ML solutions to improve Delivery marketplace efficiency while delivering magical user experience
• Lead ML engineers, provide technical leadership and vision for the team.

Basic Qualifications

• PhD or equivalent in Computer Science, Engineering, Mathematics or related field AND 2-years full-time Software Engineering work experience OR 5-years full-time Software Engineering work experience, WHICH INCLUDES 3-years total technical software engineering experience in one or more of the following areas:

  • Programming language (e.g. C, C++, Java, Python, or Go)
  • Large-scale training using data structures and algorithms
  • Modern machine learning algorithms (e.g., tree-based techniques, supervised, deep, or probabilistic learning)
  • Machine Learning Software such as Tensorflow/Pytorch, Caffe, Scikit-Learn, or Spark MLLib

• Experience with SQL and database systems such as Hive, Kafka, Cassandra, etc

• Experience in the development, training, productionization and monitoring of ML solutions at scale.

Preferred Qualifications

• Experience in a technical leadership role and mentoring junior engineers.
• Experience in modern deep learning architectures and probabilistic models.
• Experience in optimization (RL / Bayes / Bandits) and online learning.
• Experience in causal inference/personalization/ranking

For San Francisco, CA-based roles: The base salary range for this role is USD$223,000 per year - USD$248,000 per year.

For Sunnyvale, CA-based roles: The base salary range for this role is USD$223,000 per year - USD$248,000 per year.