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Adobe

Machine Learning Engineer /Firefly

Adobe, San Francisco, CA, United States

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Qualifications

  • Master's degree or above in Computer Science or a related field, or equivalent practical experience
  • Strong proficiency in Python and PyTorch
  • Solid foundation in computer science fundamentals
  • Experience with distributed training and its common strategies
  • Experience working with large and complex code bases, employing API design techniques to maintain clean and maintainable code
  • Excellent communication and collaboration skills
  • Think creatively about troubleshooting, debugging, and solving complex, hard-to-reproduce problems
  • Proficiency in SDK development and architecture
  • Familiarity with container orchestration technologies like Kubernetes and EC2

Responsibilities

  • Design and implement reusable and scalable training framework that supports different deep learning models in large-scale and distributed environments
  • Design, architect, implement, and optimize the various components of the training framework, primarily using Python, PyTorch, used by numerous internal users
  • Collaborate closely with ML Researchers and Machine Learning engineers to accelerate the training of the cutting-edge ML models
  • Lead projects from scoping requirements to launch, ensuring ongoing support
  • Identify and resolve usability, extensibility, scalability issues specific to the framework
  • Stay updated with the latest test, development, and deployment practices, and actively share knowledge with the team and community

Benefits

  • The U.S. pay range for this position is $135,200 -- $250,900 annually
  • 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
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