ML Infrastructure Engineer

San Jose

Adobe

Adobe is changing the world through digital experiences. We help our customers create, deliver and optimize content and applications.

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Our Company

Changing the world through digital experiences is what Adobe’s all about. We give everyone—from emerging artists to global brands—everything they need to design and deliver exceptional digital experiences! We’re passionate about empowering people to create beautiful and powerful images, videos, and apps, and transform how companies interact with customers across every screen. 

We’re on a mission to hire the very best and are committed to creating exceptional employee experiences where everyone is respected and has access to equal opportunity. We realize that new ideas can come from everywhere in the organization, and we know the next big idea could be yours!


 

Responsibilities:

  • Design, architect and build cloud ML platform solutions related but not limited to resource management, monitoring, allocation, and job scheduling.
  • Design, architect and build reliability, observability and utilization infrastructure for cloud computing resources.
  • Collaborate with data platform engineers and architects to seamlessly integrate low latency data pipelines into the ML platform for model training.
  • Collaborate with machine learning and data scientists to identify and resolve requirements in order to improve the training cost and turnaround time on the ML platform.
  • Monitor machine learning platform performance and modify infrastructure to fit fluid cloud resource needs.
  • Write high quality, product level code that is easy to maintain and test following standard methodologies.

Key skill requirements:

  • Proficiency in at least two of: Linux, Ansible, Docker, Kubernetes (5+ yrs)
  • Expert in Python and or C++
  • Experience in distributed computing (7+ yrs)
  • Experience in HDFS, Spark, Presto (3+ yrs)
  • Experience working with AWS or similar cloud infrastructure (5+ yrs)
  • Experience with HW resource management for ML training and/or deployment
  • B.S., M.S, or Ph.D. in Computer Science, Computer Engineering or a related area

Our compensation reflects the cost of labor across several  U.S. geographic markets, and we pay differently based on those defined markets. The U.S. pay range for this position is $124,000 -- $234,200 annually. Pay within this range varies by work location and may also depend on job-related knowledge, skills, and experience. Your recruiter can share more about the specific salary range for the job location during the hiring process.

At Adobe, for sales roles starting salaries are expressed as total target compensation (TTC = base + commission), and short-term incentives are in the form of sales commission plans.  Non-sales roles starting salaries are expressed as base salary and short-term incentives are in the form of the Annual Incentive Plan (AIP).

In addition, certain roles may be eligible for long-term incentives in the form of a new hire equity award.

Adobe will consider qualified applicants with arrest or conviction records for employment in accordance with state and local laws and “fair chance” ordinances.

Adobe is proud to be an Equal Employment Opportunity and affirmative action employer. We do not discriminate based on gender, race or color, ethnicity or national origin, age, disability, religion, sexual orientation, gender identity or expression, veteran status, or any other applicable characteristics protected by law. Learn more.
 

Adobe aims to make Adobe.com accessible to any and all users. If you have a disability or special need that requires accommodation to navigate our website or complete the application process, email accommodations@adobe.com or call (408) 536-3015.

Adobe values a free and open marketplace for all employees and has policies in place to ensure that we do not enter into illegal agreements with other companies to not recruit or hire each other’s employees.

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Tags: Ansible AWS Computer Science Data pipelines Docker Engineering HDFS Kubernetes Linux Machine Learning ML infrastructure Model training Pipelines Python Spark

Perks/benefits: Equity / stock options

Region: North America
Country: United States

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