> Markdown version of [/jobs/ext/3638360-staff-machine-learning-engineer](https://www.wearedevelopers.com/jobs/ext/3638360-staff-machine-learning-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Staff Machine Learning Engineer - **Company:** Uber - **Location:** Sunnyvale, CA, United States (Remote available) - **Experience:** Expert - **Salary:** $209,000.0 - **Contract:** Permanent contract - **Skills:** Computer Engineering, Machine Learning, Tensorflow, Reinforcement Learning, Pytorch, Backend, Information Technology, Marketplace - **Published:** October 8, 2026 - **Apply:** https://www.techcareers.com/job.asp?id=3421892459&tx=FK3936FFF&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54 ## About the Role 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., * 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)., * Product 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 ## Description This 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.