Staff Machine Learning Engineer

Job-ID: 160305Category: EngineerLocation: San Francisco, CA, United States; Chicago, IL, United States; Seattle, WA, United States; Sunnyvale, CA, United States; New York City, NY, United StatesSchedule: Full time, Level 5BPosted: 2026-07-31About the RoleUber Freight Marketplace is building the next generation of logistics technology by leveraging Uber’s proven marketplace playbook to freight. As part of a small, high-impact team, you'll help bring expertise from Uber’s mobility and delivery marketplaces into a rapidly evolving industry, developing pricing, matching, recommendation, and optimization systems that will disrupt the freight industry ($1T TAM). Uber Freight is at a very early stage, with just 0.4% of the pie now, and it's a rare opportunity to solve challenging marketplace problems with AI/ML and marketplace optimization while shaping how the freight industry transforms.We are looking for a highly motivated Machine Learning Engineer to join Uber’s Marketplace team to modernize the Uber Freight marketplace team. It is a fascinating area with challenges in predictive modeling, causal inference, constrained optimization, reinforcement learning, marketplace design, etc. The business is about to elevate and this role has a huge growing opportunity.What You'll DoThis role requires end to end ownership for the ML models in UF marketplace (cost prediction, booking probability, demand elasticity, etc.). While your job is mostly about model development, you will work with backend engineers together to put them in production and make sure they work as expected.Basic Qualifications 6+ years of experience developing ML models to solve business problem.Bachelor’s degree in Computer Science, Computer Engineering, or related fields.Familiar with modern AI/ML frameworks (e.g., PyTorch). Preferred QualificationsProduct experience will be a big plus for this role. Adaptive development of ML models to the business context is critical. Previous experience with state-of-the-art marketplace technology is preferred.Experience with causal inference and constrained optimizationResponsibilitiesFor Chicago, IL-based roles: The base salary range for this role is USD $209,000 per year - USD $232,000 per year.For New York City, NY-based roles: The base salary range for this role is USD $232,000 per year - USD $258,000 per year.For San Francisco, CA-based roles: The base salary range for this role is USD $232,000 per year - USD $258,000 per year.For Seattle, WA-based roles: The base salary range for this role is USD $232,000 per year - USD $258,000 per year.For Sunnyvale, CA-based roles: The base salary range for this role is USD $232,000 per year - USD $258,000 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.About the companyReady to Ride?This isn't the kind of place where you follow a playbook — it's where you help write one. If you're driven by impact, energized by challenge, and ready to shape how the world moves — we'd love to hear from you.You may be eligible for bonuses, equity, and other compensation, as well as a range of benefits. Explore our benefits.Offices remain key to collaboration and Uber's culture. Unless approved for full remote work, employees must spend at least 50% of their time in-office. Some roles, like those at greenlight hubs, require full-time in-office presence. Ask your Recruiter for details about this role's requirements.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.