The At Scale Validation Data and AI (Artificial Intelligence) Frameworks Engineer conducts design and development to build and optimize AI software.

Responsibilities include, but are not limited to:

• Designing, developing, and optimizing for AI frameworks (e.g., OpenVINO) and to contribute to external frameworks (e.g., TensorFlow, PyTorch).
• Implementing various distributed algorithms such as model/data parallel frameworks, parameter servers, dataflow based asynchronous data communication in machine learning, and/or deep learning frameworks.
• Transforming computational graph representation of neural network model, and developing machine learning and/or deep learning primitives in mathematical libraries.
• Profiling distributed deep learning models to identify performance bottlenecks and proposes solutions across individual component teams.
• Optimizing code for various computing hardware backends, and interacting 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. Preferred qualifications are in addition to the minimum requirements and are considered a plus factor in identifying top candidates. Experience listed below would be obtained through a combination of your school work/classes/research and/or relevant previous job and/or internship experiences.

Minimum Qualifications:

• Candidate must possess a Bachelor's degree or higher in Machine Learning, Data Science, Financial Engineering, or related STEM program (documentation related to Bachelor's degree completion will be required). 
• 3+ months of programming experience in: Python, Java, C, or similar language.
• 3+ months of data analysis or machine learning code development expertise.