What are the responsibilities and job description for the Sr. Program Manager, AI Data Operations position at Uber?
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.
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.
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.
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.
- 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.
- Exposure to LLMs, foundation model training and human in the loop (HITL) operations.
- Familiarity with annotation for multimodal inputs (e.g., Audio, Video, Image, Text, Documents, OCR based forms etc)
- Experience of working in customer facing roles
- Experience managing budgets, metrics, and KPIs across distributed teams.
- Knowledge of quality scoring frameworks, defining quality rubrics and QA loop design.
- Technical background (e.g., in ML, data science, or engineering) is a plus.
Salary : $162,000 - $180,000
