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.

Uber's mission is to reimagine the way the world moves for the better. Here, bold ideas create real-world impact, challenges drive growth, and speed fuels progress. What moves us, moves the world - let's move it forward, together.

Uber is proud to be an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing this form.

Offices continue to be central to collaboration and Uber’s cultural identity. Unless formally approved to work fully remotely, Uber expects employees to spend at least half of their work time in their assigned office. For certain roles, such as those based at green-light hubs, employees are expected to be in-office for 100% of their time. Please speak with your recruiter to better understand in-office expectations for this role.