Sr Machine Learning Engineer- Maps Optimization

Build large-scale machine learning systems that directly improve how people move. As a Sr Machine Learning Engineer on Uber's Maps Optimization team, you will design, deploy, and maintain high-throughput, low-latency prediction models and APIs that power map experiences such as location search, ETA calculation, and routing across millions of trips worldwide. The role blends applied ML with production engineering, with an emphasis on measurable gains in logistical efficiency.

What you’ll do

• Develop and deploy end-to-end machine learning models and the infrastructure needed to optimize Uber map-related applications
• Design and maintain high-throughput, low-latency prediction systems and APIs that handle hundreds of billions of daily requests
• Test and iterate on novel approaches to improve logistical efficiency across Uber product verticals
• Collaborate with product managers, scientists, designers, and engineers to deliver solutions to real-world challenges

What you’ll bring

• 5+ years of experience in machine learning, or 2+ years with a PhD
• 2+ years in one or more of: machine learning, artificial intelligence, optimization, signal processing, operational research, or related technical fields
• Experience building, debugging, and scaling distributed data processing and ML pipelines (for example: Apache Spark, Hive, Presto, Michelangelo)
• Knowledge of development and debugging in Java, Scala, or Golang, plus experience with scripting languages such as Python and/or shell scripts
• Technical leadership experience, including owning projects and defining technical direction
• Bachelor’s degree in Computer Science, Computer Engineering, a relevant technical field, or equivalent practical experience

Technologies you may work with

• Apache Spark, Hive, Presto, Michelangelo
• Java, Scala, Golang
• Python, shell scripts

Compensation and benefits

Salary range: USD 202,000 - 224,000 per year.

• Eligible to participate in Uber’s bonus program
• May be offered an equity award and other types of compensation
• Eligible to participate in a 401(k) plan
• Eligible for various benefits

Preferred qualifications

• Experience architecting large-scale, production software applications
• Experience productionizing applied machine learning solutions (for example: graph/graphless prediction, learning to rank)
• Master’s degree or PhD in Computer Science or a related technical field

Location and work setup

Sunnyvale, CA (hybrid)

• Unless approved for full remote work, employees must spend at least 50% of their time in-office
• Ask your Recruiter for details about this role’s specific requirements