AI Frameworks Engineer

Intel Corporation•Hillsboro, OR

2d•$133,410 - $240,710•Hybrid

About The Position

As an AI Frameworks Engineer, you will design and develop AI software to optimize AI frameworks. You will contribute to developing and optimizing advanced AI frameworks, implement distributed algorithms, and collaborate with researchers to deliver high-performance solutions. Your work will enhance Intel's AI capabilities and advance machine learning and deep learning technologies. The role is part of a group advancing AI solutions through optimized frameworks and libraries that accelerate artificial intelligence applications. The team supports AI performance breakthroughs and Intel's mission to shape the future of computing and empower customers globally. This role is eligible for Intel's hybrid work model, allowing employees to split time between working on-site at an assigned Intel site and off-site. Primary locations are Folsom, California, and Hillsboro, Oregon. The annual US target compensation range is $133,410 to $240,710. Individual pay depends on work location and factors including job-related skills, experience, and relevant education or training.

Requirements

Bachelor's degree in Computer Science, Electrical Engineering, or a related field, with at least 1 year of experience in AI frameworks development and optimization, or a master's degree in a relevant field.
At least 6 months of experience with programming languages such as Python or C++.
At least 6 months of experience with AI frameworks such as TensorFlow, PyTorch, or OpenVINO.
At least 6 months of experience with algorithmic and mathematical skills applicable to machine learning and deep learning.
Strong communication and presentation skills.
Strong organizational and planning skills.
Ability to work independently in a highly matrixed structure.

Nice To Haves

Master's degree in a relevant field with at least 2 years of related experience, or a Ph.D.
Experience optimizing code for hardware backends such as CPUs, GPUs, or accelerators.
Familiarity with distributed computing techniques and tools for AI applications.
Experience with graph-based computation models and performance profiling tools.
Strong communication skills and experience collaborating in cross-functional teams.
Passion for driving innovation and solving complex technical challenges in the AI domain.

Responsibilities

Design, develop, and optimize AI frameworks such as OpenVINO, TensorFlow, and PyTorch.
Implement and enhance distributed algorithms, including model/data parallel frameworks, parameter servers, and asynchronous data communication.
Transform computational graph representations of neural network models to improve performance.
Develop high-performance machine learning and deep learning primitives within mathematical libraries.
Profile distributed deep learning models to identify bottlenecks and propose effective solutions.
Optimize code across a variety of computing hardware backends to maximize performance.
Collaborate with researchers to integrate advancements in machine learning and deep learning into frameworks.