Senior Technical Program Manager (AI/ML)
ARCHIVED
We can't find an active application page for this role right now. It may reopen or be listed elsewhere. Use Next Steps to search for an active apply link and similar live jobs.
Job Summary: We seek a Technical Program Manager to lead data annotation programs for AI research. This role combines program management, data operations, and AI/ML to deliver scalable, high-quality data labeling aligned with research and product needs. You will work with researchers, data scientists, ML engineers, product managers, and vendors to manage the full lifecycle of large-scale data curation—from planning and execution to delivery and evaluation. Job Location: San Francisco, CA Mountain View, CA Seattle, WA Key Responsibilities: Drive end-to-end data annotation programs, including scoping, delivery, and post-mortem analysis. Collaborate with AI research leaders, researchers, data scientists, ML engineers, and product managers to define data needs, metrics, and guidelines. Manage vendors and internal teams, handling contracts, SLAs, quality standards, and throughput. Design quality control pipelines, annotation tools, and feedback loops for scalable data quality. Partner with engineering to enhance annotation infrastructure, workflows, and data pipelines. Support data governance, including privacy, security, ethics, and compliance. Track metrics like cost, quality, speed, and volume; report progress to stakeholders. Coordinate internal adoption of AI products via onboarding, workflows, and change management. Standardize processes to measure, monitor, and improve data quality across teams and datasets. Engage customers and partners in workshops, pilots, and feedback for continuous improvement. Key Requirements: Bachelor's or Master's in Computer Science, Data Science, Machine Learning, Information Systems, or equivalent experience. 7+ years in technical program management, project management, or operations in data/AI/ML environments. Strong knowledge of ML workflows, data pipelines, and annotation lifecycles. Experience leading large-scale data labeling or collection with third-party vendors. Familiarity with big data platforms and data warehousing. Advanced SQL skills for analytics, tracking, forecasting, visualization, reports, and dashboards. Proven ability to perform root cause analysis on data and processes for business insights. Excellent organizational, problem-solving, communication, negotiation, and analytical skills. Experience documenting standard operating procedures. Ability to influence cross-functional teams and deliver complex projects on time with high quality. Self-motivated; thrives independently and in teams. Preferred: Knowledge of GPU technology in generative AI/ML. Familiarity with Apache Spark, Delta Lake, MLflow.