[Skip to main content](#main-content) [OpenNash Jobs](https://jobs.opennash.com/) [Hiring report](/reports/hiring/) · [All Uber jobs](https://jobs.opennash.com/companies/uber/) · [Search jobs](/search/) Uber · San Francisco, CA # Staff Machine Learning Engineer - Applied AI San Francisco, CA, United States Full-time Senior individual contributor $232,000 per year Data & Analytics Listed on Uber’s official careers site. Posted July 17, 2026. Check that it is still open and apply there. [Apply on Uber’s careers site →](https://iaziqy.fa.ocs.oraclecloud.com/hcmUI/CandidateExperience/en/sites/UberCareers/job/145860) [OpenNash Jobs](https://jobs.opennash.com/) / [Uber](https://jobs.opennash.com/companies/uber/) / Staff Machine Learning Engineer - Applied AI ## Job description ### About the Team The Applied AI team collaborates with product teams across Uber to deliver innovative AI solutions for core business problems. We work closely with engineering, product and data science teams to understand core business problems and the potential for AI solutions, then deliver those AI solutions end-to-end. Key areas of expertise include Personalization, Generative AI, Computer Vision, ML Optimization and Geospatial AI. ### About the Role We are building AI-native discovery experiences across Mobility and Delivery. Search, recommendations, and conversational AI are central to how millions of users discover rides, restaurants, grocery items, and retail products every day. We are hiring a Staff ML Engineer (IC6) to define and lead the foundation model strategy powering these experiences. At this level, you will not just build models — you will shape technical direction across teams, influence product strategy, and deliver measurable impact at global scale. What the Candidate Will Do Own the end-to-end technical strategy for foundation models across Search, Recommendations, and Conversational AI. Drive architecture decisions that influence multiple product surfaces (Eats, Grocery, Retail, Mobility). Lead cross-team initiatives spanning Retrieval, Ranking, Personalization, and LLM-powered assistants. Define long-term investment areas (build vs fine-tune vs partner models). Mentor senior engineers and act as a technical multiplier across the org. ### Basic Qualifications Masters degree or Ph.D in Computer Science, Engineering, Mathematics 8+ years of ML experience, including significant work on large-scale deep learning systems. Demonstrated ownership of high-impact ML systems in search, recommendations, or conversational AI. Deep expertise in transformers, retrieval systems, ranking, and embedding architectures. Strong experience with PyTorch and distributed training. Track record of influencing technical direction across teams. Strong product intuition and ability to connect model improvements to business outcomes. ### Preferred Qualifications Experience leading multi-team ML initiatives. Defined long-term technical roadmaps adopted across orgs. Elevated engineering standards through mentorship and technical leadership. ~~ ~~ ## Responsibilities ### 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 Sunnyvale, CA-based roles 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. ## At a glance - Posted by the employer: Jul 17, 2026 - First seen by OpenNash: Oct 19, 2026 - Last checked: Oct 19, 2026 - Listed for: 94 days - Location: San Francisco, CA, United States - Employment type: Full-time - Pay: $232,000 per year[Apply on Uber’s careers site →](https://iaziqy.fa.ocs.oraclecloud.com/hcmUI/CandidateExperience/en/sites/UberCareers/job/145860) ## More jobs at Uber ### [Manager II, Analytics - Financial Operations](https://jobs.opennash.com/companies/uber/jobs/f5cd588297da8b1fc82e/) San Francisco, CA, United States ### [Sr Machine Learning Engineer](https://jobs.opennash.com/companies/uber/jobs/fae99b509ece74d29600/) San Francisco, CA, United States ### [Sr Machine Learning Engineer- Maps Optimization](https://jobs.opennash.com/companies/uber/jobs/3862e7851681f1a10554/) San Francisco, CA, United States ### [Sr People Analytics Analyst](https://jobs.opennash.com/companies/uber/jobs/201c16c0e24b819adb8d/) San Francisco, CA, United States ### [Sr Staff Machine Learning Engineer - Uber AI Solutions](https://jobs.opennash.com/companies/uber/jobs/7900e1374bfb8271c25c/) San Francisco, CA, United States ## Similar jobs at other companies ### [Senior Staff Engineer, Machine Learning Engineering ( On-device Learning SW)](https://jobs.opennash.com/companies/qualcomm/jobs/d561df305202050c72d5/) Qualcomm · San Diego, California, United States of America ### [Staff Machine Learning Software Engineer](https://jobs.opennash.com/companies/qualcomm/jobs/1c015546a5addf14b5ac/) Qualcomm · San Diego, California, United States of America ### [AI Machine Learning Engineering Staff](https://jobs.opennash.com/companies/lockheed-martin/jobs/a50fa89c9d061673bf86/) Lockheed Martin · Virtual Three, TX ### [A/AI Machine Learning Engineering Staff - Clearance Required](https://jobs.opennash.com/companies/lockheed-martin/jobs/fee14b837ea19e8438a2/) Lockheed Martin · Huntsville, AL ### [Senior Machine Learning Engineer](https://jobs.opennash.com/companies/microsoft/jobs/a28bc03521860e161cf2/) Microsoft · United States, Massachusetts, Cambridge OpenNash lists jobs from employers’ own careers sites and does not handle applications. Dates come from the employer where stated; “first seen” and “last checked” are our own observations. OpenNash Jobs · Official listings with dates and links to the employer. [Weekly hiring report](/reports/hiring/) · [Methodology](/methodology/)