Dir, Machine Learning Eng

Adobe Systems
San Jose
Workplace: OnsiteFull timeFunction: Data Science & Machine LearningEducation: bachelorsSkills: ["Leadership","Communication","Team management","Problem-solving"]

Lead a team of applied scientists and data engineers within Adobe Experience Platform to design, build, and maintain core AI/ML capabilities for a petabyte-scale data lakehouse. Drive strategic transformation of data engineering toward AI/ML integration, establish best data and engineering practices, and recruit and develop top talent while ensuring governance and ethical use of AI across the platform.

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Adobe Systems
Adobe Systems
8 months ago

Dir, Machine Learning Eng

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 17 hours agoStatus: Closed

Job Summary

Lead a team of applied scientists and data engineers within Adobe Experience Platform to design, build, and maintain core AI/ML capabilities for a petabyte-scale data lakehouse. Drive strategic transformation of data engineering toward AI/ML integration, establish best data and engineering practices, and recruit and develop top talent while ensuring governance and ethical use of AI across the platform.
Location: San Jose
Workplace: Onsite
Employment Type: Full time
Job Function: Data Science & Machine Learning

Key Responsibilities

  • •Technical Leadership: 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)
  • •Strategic Leadership: 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; provide strong leadership to the engineering team, fostering collaboration, innovation, and continuous improvement
  • •Define and Maintain the best Data, ML and Engineering practices: Drive technical excellence, operational maturity, and code quality within your team; stay up-to-date with emerging trends to ensure best practices
  • •Talent Scouting and Training: Attract, recruit, hire, and develop a high-performing group with the right mix of skills to support the AI/ML, data and operational excellence needs
  • •Oversee data engineering initiatives to enable AI/ML-driven applications and governance

Key Requirements

  • •Over 10 years of experience in software engineering with at least 5 years focused in designing machine learning solutions with direct application in the data engineering space
  • •Ability to lead and inspire a team, excellent interpersonal skills, and the 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, with hands-on experience in model development, deployment, and optimization complemented with a good understanding of the big data technologies and challenges
  • •Strategic thinking capabilities, with a proven track record of leveraging AI to solve complex business challenges and drive growth
  • •Typically requires a Master’s degree in applied machine learning, artificial intelligence, or data science. A PhD is preferred
Experience:AI/MLData engineeringAdobe Experience PlatformBig data
Education:Bachelor's
Skills:LeadershipCommunicationTeam managementProblem-solving
Tech Stack:SparkKubernetesMachine learningAIData lakehouseBig dataModel developmentDeploymentOptimization

Company Brief

Adobe Systems
Provides creative, marketing, and document management software and cloud services, including Photoshop, Illustrator, Acrobat, and the Adobe Experience Cloud, serving creative professionals, enterprises, and governments worldwide.
Industry: SaaS
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Public Company
Valuation: Public Company (Market Cap in USD)
Funding: IPO / Publicly Listed
Headquarters: San Jose, United States
Founded: 1982
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