Hardware Machine Learning PhD Research Internship
ML Hardware Research
Likely openWe list a role only while we believe it is still open. Confirm on the posting before you apply.
What stands out
- Pay is stated up front — $225,000. Most postings never say.
- Nobody had applied when this was listed — you would be near the front of the queue.
- Posted in the last 24 hours.
The gist
This PhD internship involves developing machine learning projects for real-world applications, working closely with hardware engineers to deploy solutions on FPGAs and ASICs. You'll evaluate cutting-edge research on quantization and neural architecture search, and present your findings to the team. Ideal for PhD students with expertise in hardware design and ML systems.
What you would actually do
- Design and implement ML projects for real-world use cases
- Collaborate with hardware engineers on FPGA/ASIC ML deployment
- Evaluate research on quantization and neural architecture search
- Present findings to team and leave a working prototype
Skills mentioned
How to apply
Internships in the US often collect hundreds of applicants within a day, so applying early matters more than applying perfectly. A half-finished application sent on the first morning beats a polished one sent on the third.
This summary was written by InternDoor from the public posting, and is not the employer's own wording. The linked posting is the source of truth — check it before you apply.