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Uber Sr Program Manager Tech in San Francisco, California

About the Role

We are seeking a seasoned Program Manager with expertise in Generative AI and data labeling to oversee the end-to-end lifecycle of data annotation programs. This role will focus on creating scalable labeling pipelines, managing annotation teams, and ensuring high-quality datasets that fuel state-of-the-art AI models.

The ideal candidate will combine a deep understanding of AI/ML workflows with exceptional organisational and leadership skills.

What the Candidate Will Do:

  • Program Strategy & Planning:

  • Define the roadmap and key objectives for data labeling projects to support generative AI initiatives.

  • Partner with stakeholders (Data Scientists, Machine Learning Engineers, and Product Managers) to identify data requirements and success criteria.

  • Pipeline Development & Management:

  • Design scalable data labeling workflows that leverage internal tools, external vendors, and automation.

  • Optimize workflows for efficiency, accuracy, and cost-effectiveness, incorporating active learning and pre-labeling techniques where appropriate.

  • Vendor & Stakeholder Management:

  • Engage and manage relationships with data labeling vendors, ensuring timely delivery and adherence to quality standards.

  • Collaborate with cross-functional teams to align labeling efforts with broader AI model development timelines.

  • Quality Assurance:

  • Implement robust quality assurance processes to validate labeled datasets against gold standards.

  • Use metrics such as inter-annotator agreement, precision/recall, and throughput to monitor quality and make improvements.

  • Budget & Resource Allocation:

  • Manage program budgets, including vendor costs and internal resources.

  • Forecast resource requirements and ensure efficient allocation to meet deadlines.

  • Compliance & Ethics:

  • Ensure compliance with data privacy regulations (e.g., GDPR, CCPA) and ethical guidelines in dataset creation.

  • Advocate for inclusive and unbiased labeling practices to mitigate bias in AI models.

Basic Qualifications:

  • Bachelor's degree in Computer Science, Data Science, or related field; or equivalent practical experience.

  • 5+ years of program/project management experience, preferably in data labeling, AI/ML, or related fields.

  • Strong knowledge of machine learning concepts, particularly around supervised learning and training data needs.

  • Experience working with data annotation platforms (e.g., Scale AI, Labelbox, Appen) and tools.

  • Proven track record of managing large-scale projects with cross-functional teams and external vendors.

Preferred Qualifications:

  • Master's degree in a technical field or MBA.

  • Experience in Generative AI, including text, image, or audio data labeling.

  • Familiarity with active learning, semi-supervised labeling, and human-in-the-loop systems.

  • Proficiency in data annotation tools and scripting languages (Python, SQL) to analyze datasets and processes.

  • Strong understanding of ethical AI and best practices for minimizing dataset bias.

  • Excellent written and verbal communication skills, with the ability to influence technical and non-technical stakeholders.

For San Francisco, CA-based roles: The base salary range for this role is USD$155,000 per year - USD$172,000 per year. You will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. You will also be eligible for various benefits. More details can be found at the following link https://www.uber.com/careers/benefits.

Uber is proud to be an Equal Opportunity/Affirmative Action 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- https://docs.google.com/forms/d/e/1FAIpQLSdb_Y9Bv8-lWDMbpidF2GKXsxzNh11wUUVS7fM1znOfEJsVeA/viewform

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