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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.
What you need to succeed:
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.
Nice to have:
Proficiency in SDK development and architecture
Familiarity with container orchestration technologies like Kubernetes and EC2
#FireflyGenAI
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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