As an ML Data Program Manager, you will be the operational backbone of our machine learning initiatives. You will own and drive the complex, cross-functional programs that deliver high-quality data—the lifeblood of our models. You will orchestrate the end-to-end data life-cycle, from defining requirements for new datasets and tooling to scaling data pipelines and ensuring our ML teams have the resources they need to innovate. This is a high-impact role for a technical, detail-oriented leader who thrives on turning ambiguous data needs into tangible, scalable solutions.

You will:

• Collaborate across cross functional groups and  align execution to meet product goals
• Partner with technical leads, product managers and technical program managers to drive execution on broad cross-functional efforts
• Lead proactive risk management efforts and contingency plans across the program landscape to deliver on the program
• Set up and sustain mechanisms that enable organizational efficiencies, and improve speed of decision making and execution
• Communicate across all levels of the organization to ensure all partners are aware of program decisions, status, and changes
• Own the details - Dive deep, identify gaps, evaluate risks and misalignment

You have:

• 8+ years of experience in engineering  program management, with at least 3+ years focused specifically on data-centric programs for machine learning
• Deep understanding of the ML model life-cycle and the critical role of data within it (e.g., data sourcing, labeling, quality evaluation)
• Proven ability to manage complex technical programs, including structuring project plans, identifying dependencies, and driving execution using Agile methodologies (e.g., Scrum)
• Demonstrated technical judgment in the ML/data domain, with the ability to facilitate trade-off discussions about data pipelines, tooling, and data quality with engineering teams
• Experience managing data annotation/labeling pipelines, either with in-house tooling or by managing third-party vendor relationships
• Exceptional communication skills, capable of articulating program strategy, status, and technical details to both executive and engineering audiences

We prefer:

• Master’s degree in a technical field, ideally related to AI/ML
• You contributed to technical decision making by analyzing trade-offs, asking the rights questions and offering alternate solutions
• Experience designing and reporting on program metrics that directly measure the impact of data quality on model performance