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.

Qualifications

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 in Machine Learning, Data Science, Financial Engineering, Telematics 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.

A candidate who accepts an offer of employment is required to present their own personal identification information and numbers for the following:  Mexican Security Number (NSS), Tax Identification Number (RFC) and CURP identification number.

Inside this Business Group

The Data Platforms Engineering and Architecture (DPEA) Group invents, designs & builds the world's most critical computing platforms which fuel Intel's most important business and solve the world's most fundamental problems. DPEA enables that data center which is the underpinning for every data-driven service, from artificial intelligence to 5G to high-performance computing, and DCG delivers the products and technologies—spanning software, processors, storage, I/O, and networking solutions—that fuel cloud, communications, enterprise, and government data centers around the world.

Work Model for this Role

This role will be eligible for our hybrid work model which allows employees to split their time between working on-site at their assigned Intel site and off-site.