Intel • Folsom, CA 95630
Job #2660537821
Job Description
As the AI landscape evolves, the emergence of generative AI has brought the cost of inference into sharp focus, identifying it as a critical bottleneck for innovation and the full utilization of AI capabilities. In the role of Staff AI Compiler Engineer, you'll be at the forefront of confronting this challenge. By contributing to the development and integration of our state-of-the-art Neural Processing Unit (NPU) compiler within the Windows Machine Learning and DirectML software stack, you will play a central role in offloading cloud inference, thereby revolutionizing the efficiency and scalability of AI applications. With your command of C++ and MLIR, you will not only enhance our NPU and its ecosystem but also redefine the parameters of what's possible in AI hardware acceleration, paving the way for broader adoption and more sustainable AI innovation.
Qualifications
You must possess the below 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.
Minimum Qualifications:
Bachelor's degree in computer science, electrical engineering, or a STEM related field with 6+ years of experience in three or more the following:
Solid background in AI frameworks and compiler construction.
High proficiency in C++ and MLIR, with a track record of applying these skills in a performance-critical environment.
Agile project management proficiency, with practical experience in tools like GitHub.
Experience in performance optimization with an emphasis on cost-effective software/hardware mapping.
Well-versed in testing frameworks and advanced methodologies.
Preferred Qualifications:
Master's degree with 4+ years of experience, OR a PhD with 2+ years of experience in a related discipline.
Practical experience in Windows driver development.
In-depth understanding of neural network workloads, with a specialization in AI model optimization for efficient inference.
Prior involvement with Generative AI integration.
Inside this Business Group
The Client Computing Group (CCG) is responsible for driving business strategy and product development for Intel's PC products and platforms, spanning form factors such as notebooks, desktops, 2 in 1s, all in ones. Working with our partners across the industry, we intend to deliver purposeful computing experiences that unlock people's potential - allowing each person use our products to focus, create and connect in ways that matter most to them. As the largest business unit at Intel, CCG is investing more heavily in the PC, ramping its capabilities even more aggressively, and designing the PC experience even more deliberately, including delivering a predictable cadence of leadership products. As a result, we are able to fuel innovation across Intel, providing an important source of IP and scale, as well as help the company deliver on its purpose of enriching the lives of every person on earth.
Other Locations
US, Hillsboro
Posting Statement
All qualified applicants will receive consideration for employment without regard to race, color, religion, religious creed, sex, national origin, ancestry, age, physical or mental disability, medical condition, genetic information, military and veteran status, marital status, pregnancy, gender, gender expression, gender identity, sexual orientation, or any other characteristic protected by local law, regulation, or ordinance.
Benefits
We offer a total compensation package that ranks among the best in the industry. It consists of competitive pay, stock, bonuses, as well as, benefit programs which include health, retirement, and vacation. Find more information about all of our Amazing Benefits here. (~~~)
Annual Salary Range for jobs which could be performed in US, California: $186,552.00-$279,772.00
*Salary range dependent on a number of factors including location and experience
Working Model
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. In certain circumstances the work model may change to accommodate business needs.
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