AI Research Scientist/Engineer
3 days ago
The Emerging Visual-AI Systems Research team at Intel Labs is seeking a highly skilled AI Research Scientist/Engineer to drive technology innovation for future industry needs. As a key member of the team, you will investigate, implement, and drive new AI optimization and acceleration techniques within Intel's HW and SW products.
Responsibilities:
- Develop and apply state-of-the-art AI model optimization techniques, including quantization, sparsity, and run-time systems.
- Collaborate with partners to drive research agenda and maintain substantial knowledge of state-of-the-art principles and theories.
- Contribute to scientific literature and the research community-at-large, and participate in the development of Intellectual Property.
Requirements:
- Bachelor's/BS with 6+ years or master's degree with 4+ years, or PHD with 2+ years of experience in Electrical Engineering, Computer Engineering, Computer Science, or a relevant engineering discipline.
- 3 or more years of experience in AI optimizations and acceleration, HPC or run-time optimizations, computer architecture, accelerator design, quantization, model compression, and generative AI models.
- Solid publication record at top-tier conferences such as NeurIPS, MLSys, ICLR, AAAI, etc.
- Parallel Multithreading programming and concurrency models.
Preferred Qualifications:
- Experience with distributed computing, AI compilers.
- Ability to drive early-stage research projects with risks and ambiguity.
What We Offer:
We offer a total compensation package that ranks among the best in the industry, including competitive pay, stock, bonuses, and benefit programs. Find more information about our benefits here: https://www.intel.com/content/www/us/en/jobs/benefits.html
Annual Salary Range for jobs which could be performed in the US: $186,552.00-$279,772.00
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. In certain circumstances the work model may change to accommodate business needs.-
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