We are seeking an experienced Technical Program Manager to lead a critical initiative building large-scale datasets for machine learning models. This role will serve as the central coordination point between our internal ML/AI, Geographic Information Systems, modeling, and technical artist teams, and external annotation partners, ensuring the successful delivery of high-quality training data that powers next-generation systems. 

Responsibilities:

• Program Management: Steward the end-to-end planning, execution, and delivery of the dataset development program, including timelines, milestones, and risk mitigation. 
• Cross-Functional Coordination: Act as the primary liaison between ML engineers, GIS engineers, technical artists, product stakeholders, and external annotation vendors. 
• Vendor Oversight: Manage vendor relationships, including onboarding, quality assurance, throughput tracking, and contract compliance. 
• Data Quality & Standards: Collaborate with ML and data teams to define annotation guidelines, quality metrics, and validation protocols. Ensure that merged datasets are reproducible. 
• Tooling & Infrastructure: Work with engineering teams to ensure annotation platforms and data pipelines are scalable, secure, and efficient. 
• Compliance & Ethics: Ensure data collection and annotation practices adhere to privacy, security, and ethical standards. 
• Documentation: Ensure that institutional knowledge exists in written form and can be transmitted easily to onboard new team members. Work with technical stakeholders to ensure that data provenance is tracked across multiple handoffs. 

• Bachelor's Degree in Computer Science, Data Science, Engineering or equivalent work experience.
• Fluency with project management tools such as Jira and Confluence. 
• Proven experience as a Technical Program Manager in AI/ML in data annotation.
• Familiarity with geospatial data types (e.g., rasters, 3D point clouds, 2D vector data) and formats (COG, OSM, GeoJSON, Shapefile, LAZ) is a plus. 
• Familiarity with database management or administration.

Desired Characteristics

• Experience managing offshore, cross-time zone distributed annotation teams.
• Comfort with the Unix command line and familiarity with Git for version control and a git server. 
• Understanding of machine learning workflows, especially supervised learning and dataset curation. 
• Background with real-time 3D rendering is preferred. 
• High attention to detail and conscientiousness. 
• Familiarity with AWS and ETL orchestration. 
• Agile or Scrum certifications. 

Additional Requirements

Fully Remote: This position has been designated as fully remote, meaning that the position is expected to contribute from a non-NBCUniversal worksite, most commonly an employee’s residence. This position is eligible for company sponsored benefits, including medical, dental and vision insurance, 401(k), paid leave, tuition reimbursement, and a variety of other discounts and perks. Learn more about the benefits offered by NBCUniversal by visiting the Benefits page of the Careers website. Salary range: $115,000 - $140,000.

We are accepting applications for this position on an ongoing basis.

As part of our selection process, external candidates may be required to attend an in-person interview with an NBCUniversal employee at one of our locations prior to a hiring decision. NBCUniversal's policy is to provide equal employment opportunities to all applicants and employees without regard to race, color, religion, creed, gender, gender identity or expression, age, national origin or ancestry, citizenship, disability, sexual orientation, marital status, pregnancy, veteran status, membership in the uniformed services, genetic information, or any other basis protected by applicable law. 

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For LA County and City Residents Only:  NBCUniversal will consider for employment  qualified applicants with criminal histories, or arrest or conviction records, in a manner  consistent with relevant legal requirements, including the City of Los Angeles' Fair Chance Initiative For Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, where applicable.