Staff Machine Learning Engineer

About 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 Qualifications6+ 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 optimization For 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-base