Machine Learning Engineer II - Optimization

About The Role

We are looking for a motivated, entrepreneurial machine learning & operations research practitioner to join our Autonomous Optimization team, which maximizes marketplace value of autonomous vehicles across Uber's Rides and Delivery platforms. As a machine learning engineer on the team, you will pioneer engineering, modeling, and optimization initiatives that bring autonomous vehicles into sustainable, general availability.

What You Will Do

• Work on solving complex inferences and optimization problems end-to-end, from problem ideation and model design to productionization
• Design and productionize high-throughput systems to deploy inferences and predictions used by millions of users per day
• Explore novel ideas towards improving the operational efficiency and value of autonomous vehicles and robots across Uber's platforms
• Partner with product managers, scientists, designers, and engineers to develop holistic solutions to real world problems
• 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
  
  

Basic Qualifications

• 2+ years of experience in the domain of machine learning, artificial intelligence, optimization, operations research, or software engineering, or a PhD in relevant domains
• Knowledge of development and debugging in Java, Scala, or Golang, and experience with scripting languages such as Python and/or shell scripts
• Bachelor's degree (or higher) in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
  
  

Preferred Qualifications

• Experience in the domains of operations research, machine learning, transportation engineering, artificial intelligence, optimization, or software engineering
• Experience developing algorithms and models for large-scale optimization problems.
• Experience with optimization packages such as Gurobi, CPLEX, and OR Tools.
• Experience designing, building, and maintaining production machine learning systems
• Experience productionizing applied machine learning solutions towards solving business or product challenges
  
  

For San Francisco, CA-based roles: The base salary range for this role is USD$167,000 per year - USD$185,500 per year. For Sunnyvale, CA-based roles: The base salary range for this role is USD$167,000 per year - USD$185,500 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. You will also be eligible for various benefits. More details can be found at the following link https://www.uber.com/careers/benefits., For San Francisco, CA-based roles: The base salary range for this role is USD$167,000 per year - USD$185,500 per year. For Sunnyvale, CA-based roles: The base salary range for this role is USD$167,000 per year - USD$185,500 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. You will also be eligible for various benefits. More details can be found at the following link https://www.uber.com/careers/benefits.