At Scale Validation Data and AI Frameworks Engineer
The At Scale Validation Data and AI Frameworks Engineer conducts design and development to build and optimize AI software.
- Designs, develops, and optimizes for AI frameworks (e.g., OpenVINO) and to contribute to external frameworks (e.g., TensorFlow, PyTorch).
- Implements various distributed algorithms such as model/data parallel frameworks, parameter servers, dataflow based asynchronous data communication in machine learning, and/or deep learning frameworks.
- Transforms computational graph representation of neural network model, and develops machine learning and/or deep learning primitives in mathematical libraries.
- Profiles distributed deep learning models to identify performance bottlenecks and proposes solutions across individual component teams.
- Optimizes code for various computing hardware backends and interacts with machine learning and/or deep learning researchers and utilizing experience with machine learning and/or deep learning frameworks.
You must possess minimum qualifications to be initially considered for this position. Experience listed below would be obtained through a combination of your school work/classes/research and/or relevant previous job and/or internship experiences.
- Candidate must possess a Bachelor's degree in Machine Learning, Data Science, Computer Engineering, or related STEM program (documentation related to Bachelor's degree completion will be required).
- 3+ months of system validation experience.
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