Dir, Machine Learning Eng

Adobe Adobe · Enterprise · San Jose, CA

Director of Machine Learning Engineering to lead a team in evolving a data platform to support AI/ML innovation, focusing on big-data management and compute abstractions within a governed trust framework.

What you'd actually do

  1. Lead a team of applied scientists and data / systems engineers in designing, building and maintaining core capabilities with Adobe Experience Platform focused on big-data management (petabytes) and compute abstractions (Spark, Kubernetes, etc)
  2. Drive the transformation of a data engineering group toward a world where AI/ML is an integral part and heavily influencing the innovation in the data engineering space.
  3. Provide strong leadership to the engineering team, fostering a culture of collaboration, innovation, and continuous improvement.
  4. Drive technical excellence, operational maturity, and code quality within your team.
  5. Up-to-date with any emerging trends to adjust the organization to always utilize the best Data, ML and Engineering practices.

Skills

Required

  • Over 10 years of experience in software engineering
  • at least 5 years focused in designing machine learning solutions
  • direct application in the data engineering space
  • Ability to lead and inspire a team
  • excellent interpersonal skills
  • capacity to communicate complex machine learning concepts and their influence / impact on the data space clearly and effectively to stakeholders at all levels.
  • A deep understanding of machine learning models, frameworks, and algorithms
  • hands-on experience in model development, deployment, and optimization
  • good understanding of the big data technologies and challenges.
  • Strategic thinking capabilities
  • proven track record of leveraging AI to solve complex business challenges and drive growth.
  • Passionate about the ethical and responsible use of AI/ML
  • ensuring solutions meet the highest standards of transparency and fairness.
  • Master’s degree in applied machine learning, artificial intelligence, or data science.

Nice to have

  • PhD is preferred

What the JD emphasized

  • direct application in the data engineering space
  • direct application in the data engineering space
  • big data technologies and challenges
  • ethical and responsible use of AI/ML
  • ethical and responsible use of AI/ML

Other signals

  • leading a team of applied scientists and data/systems engineers
  • designing, building, and maintaining core capabilities
  • big-data management (petabytes) and compute abstractions
  • drive the transformation of a data engineering group toward a world where AI/ML is an integral part
  • instilling the intelligence needed in the data lakehouse, data modeling and compute core platform capabilities