Lead and grow a distributed team focused on training data for Generative AI.
Define and execute strategy for acquiring, processing, curating, annotating, versioning, and ensuring quality of large-scale datasets for Adobe Firefly.
Build and maintain scalable, efficient data pipelines across the training data lifecycle.
Collaborate with researchers, ML engineers, and PMs to align on data needs for new models.
Champion data diversity, bias mitigation, and ethical AI practices.
Evaluate and integrate tools and methodologies to enhance infrastructure and workflows.
Influence model development through insights on data quality and availability.
Provide technical leadership and foster a culture of innovation.
Partner across teams to align data priorities and share best practices.

Requirements

Master’s/Ph.D. in CS, Data Science, Engineering, AI/ML, or related field—or equivalent experience.
5+ years in engineering leadership, managing data infrastructure or ML data ops teams.
Deep understanding of ML data lifecycles, especially for generative models (GANs, diffusion).
7+ years building and optimizing large-scale ETL/ELT pipelines and data warehousing.
Expertise in data quality, governance, versioning, and annotation platforms.
Proficiency with cloud data tech (AWS, Azure, GCP, Spark, Databricks, Snowflake).
Strong grasp of data privacy, security, and ethical AI principles.
Excellent leadership and cross-functional collaboration skills.
Experience with large-scale image/video datasets.

Benefits

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Applicant Tracking System Keywords

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Hard Skills & Tools

data pipelinesETLELTdata warehousingdata qualitydata governancedata versioningdata annotationgenerative modelsmachine learning

Soft Skills

leadershipcross-functional collaborationinnovationdata diversitybias mitigationethical AI practices

Certifications

Master’s degreePh.D.