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Sr Staff ML Engineer - Applied AI

Machine Learning, Engineering
in San Francisco, California
- Full Time

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, 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 Senior Staff ML Engineer to define the multi-year technical vision and architecture for foundation models powering these experiences.

The Uber Foundation Model would serve as the common semantic backbone that enables Uber to understand users, places, merchants, items, and behavioral patterns in a unified way. By building a shared representation layer and continuously improving it with cross-LOB signals, Uber ensures that intelligence compounds rather than fragments. This foundation powers personalization, search, agents, automation, and decision systems across Mobility, Delivery, and future surfaces.

At this level, you will set the long-term technical direction for the organization, drive alignment on product and engineering strategy at the executive level, and deliver step-change measurable impact at global scale.

What the Candidate Will Do:

  • Define and champion the multi-year technical vision and architecture for foundation models across Search, Recommendations, and Conversational AI.
  • Set the architectural standard and drive system design for critical, high-leverage ML platforms across Mobility and Delivery.
  • Lead cross-team initiatives spanning Retrieval, Ranking, Personalization, and LLM-powered assistants, resolving complex technical trade-offs across organizational boundaries.
  • Define long-term investment areas (build vs fine-tune vs partner models) with clear business rationale and long-term viability.
  • Provide principal-level technical leadership, mentoring Staff and Senior Staff engineers, and setting the bar for technical excellence across the entire AI organization.

Basic Qualifications:

  • Masters degree or Ph.D in Computer Science, Engineering, Mathematics
  • 12+ 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.
  • Proven ability to set the technical strategy for a large organization and influence product roadmaps at the executive level.
  • Strong product intuition and ability to connect model improvements to business outcomes.

Preferred Qualifications:

  • Track record of successfully launching multi-year, multi-org ML initiatives that drove step-change business outcomes.
  • Successfully championed and driven the adoption of multi-year technical roadmaps across multiple large engineering organizations.
  • Elevated engineering standards through mentorship and technical leadership, establishing org-wide best practices.

For San Francisco, CA-based roles: The base salary range for this role is USD$267,000 per year - USD$297,000 per year.

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. More details can be found at the following link https://jobs.uber.com/en/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.


See our Candidate Privacy Statement

Uber is proud to be an equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, Veteran Status, or any other characteristic protected by law.

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선호하는 언어 선택

아랍어, العربية아삼어, অসমীয়া아제르바이잔어, Azərbaycanca불가리아어, Български벵골어, বাংলা카탈로니아어(스페인), Català (Espanya)체코어, Čeština덴마크어, Dansk독일어, Deutsch그리스어, Ελληνικά영어, English스페인어, Español (Internacional)스페인어, Español (Argentina)스페인어, Español (Chile)스페인어, Español (Colombia)스페인어, Español (Costa Rica)스페인어(유럽), Castellano스페인어, Español (Honduras)스페인어, Español (México)스페인어, Español (Uruguay)에스토니아어, Eesti핀란드어, Suomi프랑스어(캐나다), Français (Canada)프랑스어, Français (France)히브리어, עברית힌디어, हिन्दी크로아티아어, Hrvatski헝가리어, Magyar인도네시아어, Bahasa Indonesia이탈리아어, Italiano일본어, 日本語조지아어, ქართული칸나다어, ಕನ್ನಡ한국어, 한국어쿠르드어, کوردی리투아니아어, Lietuvių라트비아어, Latviešu말라얄람어, മലയാളം마라티어, मराठी노르웨이어(보크말), Norsk Bokmål네팔어, नेपाली네덜란드어, Nederlands펀잡어, ਪੰਜਾਬੀ폴란드어, Polski포르투갈어(브라질), Português (Brasil)포르투갈어(유럽), Português (Portugal)루마니아어, Română러시아어, Русский싱할라어(스리랑카), සිංහල슬로바키아어, Slovenčina슬로베니아어(슬로베니아), Slovenščina스웨덴어, Svenska스와힐리어, Kiswahili타밀어, தமிழ்텔루구어, తెలుగు태국어, ไทย터키어, Türkçe우크라이나어, Українська우르두어, اردو베트남어, Tiếng Việt중국어, 简体中文중국어(홍콩[중국 특별행정구]), 香港中文중국어(대만), 繁體中文