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Uber
Sr. Program Manager, AI Data Operations
2 months ago• San Francisco, CA (+1 more)Sunnyvale, CA
Viewed on February 1, 2026
Apply on company site
About Us
Uber is changing how people think about transportation, part of the logistical fabric of 600+ cities - giving people what they want when they want it.
- Size: 10000+ employees
- Industry: Technology
View Company Profile:
About the Role:
Uber AI Solutions is one of Uber's biggest bets with the ambition to build one of the world's largest data foundries for AI applications and evolve into a platform of choice for a variety of online tasks. AI Data Labelling operations is one of the core functional teams within Uber AI Solutions with the responsibility to oversee the end-to-end lifecycle of the data annotation programs for B2B clients.
As a seasoned program manager for AI data operations, you will be responsible for defining the programs and its key objectives to support LLM model training. You will drive cross-functional efforts across Operations, Product, Eng and Legal to define the Program-level Ops strategy, define scalable data labeling workflows leveraging internal tools, external vendors, and automation.
The role will also shape task/ product/ feature launches and improvements by working closely with global Supply, product, and engineering teams.
You will be required to work with a geographically diverse team.
True to Uber values, we are looking for a leader with an "owner" and "go-get-it" mindset who is ready to scale a brand new business line. You need to be customer-obsessed and "build with heart" while demonstrating ability to build the vision as well as roll up the sleeves and get into action to "see the forest and the trees".
If you're passionate about re-imagining the gig marketplace for skilled workers and impacting the lives of millions of skilled gig workers while working with a top-tier team, this is the opportunity for you
What the Candidate Will Do:
As a Senior Program Manager for AI Data Labeling, you will lead cross-functional initiatives to build, scale, and optimize data annotation programs critical to AI model performance.
You'll own program delivery across internal teams, vendor partners, and ML stakeholders to ensure high-quality labeled datasets are delivered on time and at scale.
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By signing up, you agree to our This role is both strategic and execution-driven: you'll define roadmaps, manage SLAs, create scalable processes, and resolve bottlenecks to ensure the labeling engine is efficient, quality-controlled, and model-aligned.
- Operational excellence
- Define and drive end-to-end execution of large-scale annotation programs across multiple data types.
- Collaborate with ML, product, and data operations teams to scope and prioritize labeling needs.
- Own vendor engagement: onboarding, SLA management, training, and quality reviews.
- Build feedback loops between annotators and model performance to inform labeling strategies.
- Create dashboards and reporting mechanisms to track labeling velocity, quality, and cost.
- Lead initiatives to improve labeling efficiency through tooling enhancements and process automation.
- Be the voice of labeling in cross-functional forums-translating model needs into operational plans.
- Customer engagement
- Drive daily, weekly and monthly meetings, business reviews and reports.
Basic Qualifications:
- 7+ years of program management experience, ideally in ML ops, data labeling, or human data operations.
- Proven track record managing multi-vendor operations or global labeling teams.
- Strong understanding of AI/ML lifecycle stages and the importance of annotated data quality.
- Experience defining SOPs, rubrics, audit mechanisms, and workflows for scalable data labeling.
- Proficient in project management tools. In addition having deep understanding on ML Operations labelling tools is added advantage
- Strong analytical and communication skills; ability to synthesize feedback from ML, ops, and product stakeholders.
Preferred Qualifications:
-
Exposure to LLMs, foundation model training and human in the loop (HITL) operations.
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Familiarity with annotation for multimodal inputs (e.g., Audio, Video, Image, Text, Documents, OCR based forms etc)
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Experience of working in customer facing roles
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Experience managing budgets, metrics, and KPIs across distributed teams.
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Knowledge of quality scoring frameworks, defining quality rubrics and QA loop design.
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Technical background (e.g., in ML, data science, or engineering) is a plus.
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For San Francisco, CA-based roles: The base salary range for this role is USD**$167,000 per year**
-
USD**$185,500 per year**.
-
For Sunnyvale, CA-based roles: The base salary range for this role is USD**$167,000 per year**
-
USD**$185,500 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. You will also be eligible for various benefits. More details can be found at the following link https://www.uber.com/careers/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.
Client-provided location(s): San Francisco, CA, Sunnyvale, CAJob ID: Uber-151029Employment Type: FULL_TIMEPosted: 2025-11-16T00:34:22Apply on company site
Perks and Benefits
Health and Wellness
- Health Insurance
- Health Reimbursement Account
- Dental Insurance
- Vision Insurance
- Life Insurance
- FSA With Employer Contribution
- Fitness Subsidies
- On-Site Gym
- Mental Health Benefits
Parental Benefits
- Fertility Benefits
Work Flexibility
- Flexible Work Hours
- Remote Work Opportunities
- Hybrid Work Opportunities
Office Life and Perks
- Casual Dress
- Pet-friendly Office
- Snacks
- Some Meals Provided
- On-Site Cafeteria
Vacation and Time Off
- Paid Vacation
- Unlimited Paid Time Off
- Paid Holidays
- Personal/Sick Days
- Sabbatical
- Volunteer Time Off
Financial and Retirement
- 401(K)
- Company Equity
- Performance Bonus
Professional Development
- Work Visa Sponsorship
- Associate or Rotational Training Program
- Promote From Within
- Mentor Program
- Access to Online Courses
Diversity and Inclusion
- Employee Resource Groups (ERG)
- Diversity, Equity, and Inclusion Program
Apply on company site
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About Uber
Reviews
3.1
10 reviews
Work Life Balance
4.2
Compensation
2.3
Culture
3.5
Career
2.0
Management
2.5
45%
Recommend to a Friend
Pros
Flexible hours and schedule
Meeting different people and cultures
Make your own hours
Cons
Inconsistent and low pay
Safety concerns with passengers
Traffic and difficult drivers
Salary Ranges
23,534 data points
Mid/L4
Mid/L4 · Data Analyst
3 reports
$209,300
total / year
Base
$161,000
Stock
-
Bonus
-
$203,580
$209,300
Interview Experience
5 interviews
Difficulty
3.0
/ 5
Duration
14-28 weeks
Offer Rate
40%
Experience
Positive 80%
Neutral 20%
Negative 0%
Interview Process
1
Application Review
2
Online Assessment
3
Recruiter Screen
4
Technical Phone Screen
5
Case Study/Analytics Test
6
Final Loop/Panel Interview
7
Offer
Common Questions
Coding/Algorithm
System Design
Behavioral/STAR
Case Study
Technical Knowledge
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