Sr Machine Learning Engineer- Maps Optimization

About the Role

The Maps Optimization team builds and maintains the foundational stack powering the full user journey on the Uber map, including location search, ETA calculation and routing. Our technology leverages advanced machine learning models and high-throughput scalable infrastructure capable of serving millions of QPS. The work of the team influences Uber’s core business performance in a meaningful way and is highly visible to the executive leadership team.

We are looking for a highly motivated, entrepreneurial machine learning engineer to join the Maps Optimization team. As a senior machine learning engineer, you will design, build, and optimize large-scale ML systems and models to improve efficiency and travel experience across millions of daily trips worldwide.

Basic Qualifications

• 5+ years of experience in the domain of machine learning, or 2+ years if you have a PhD
• 2+ years of experience in one or more of the following areas: machine learning, artificial intelligence, optimization, signal processing, operational research, or related technical fields
• Experience developing, debugging, and scaling distributed data processing and ML pipelines (e.g., Apache Spark, Hive, Presto, Michelangelo)
• Knowledge of development and debugging in Java, Scala, or Golang, and experience with scripting languages such as Python and/or shell scripts
• Experience in technical leadership, working with teams, owning projects, defining and setting technical direction for projects
• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience

Preferred Qualifications

• Experience architecting large scale, production software applications
• Experience productionizing applied machine learning solutions (e.g., graph/graphless prediction, learning to rank) toward solving complex ML challenges
• Masters degree or PhD in Computer Science or a related technical field

What the You Will Do

• Develop and deploy end-to-end machine learning models and infrastructure to optimize Uber map related applications
• Design and maintain high-throughput, low-latency prediction systems and APIs handling hundreds of billions of daily requests
• Explore novel ideas towards improving Uber's logistical efficiency across its product verticals
• Partner with product managers, scientists, designers, and engineers to develop holistic solutions to real world problems

You might thrive in this position if you:

• Have extensive prior experience building and maintaining production machine learning systems
• Own problems end-to-end, and are willing to pick up whatever knowledge you're missing to get the job done
• Have the ability to move fast in an environment where things are sometimes loosely defined and may have competing priorities or deadlines

For San Francisco, CA-based roles: The base salary range for this role is USD $202,000 per year - USD $224,000 per year.

For Sunnyvale, CA-based roles: The base salary range for this role is USD $202,000 per year - USD $224,000 per year.

For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits.