Applied Deep Learning Research Interview Experience - United States
Process
Two rounds of phone interviews were conducted.
The first was with the VP of Applied DL research.
We talked about my recent projects in DL, specifically in applied medical DL. There were some general questions on my routine model architecture design, including regularization, training, and parameter tuning.
I also asked about ongoing projects.
The second round was with a senior engineer from the same team. It was a coding interview on CoderPad (the research team uses mostly Python).
There were two questions. The first was the implementation of the equivalent of scipy.stats.rv_discrete.
Questions
The second round was with a senior engineer from the same team. It was a coding interview on CoderPad (the research team uses mostly Python).
There were two questions. The first one was basically the implementation of the equivalent of scipy.stats.rv_discrete.
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Interview Statistics
The following metrics were computed from 2 interview experiences for the Nvidia Applied Deep Learning Research role in United States.
Success Rate
Nvidia's interview process for their Applied Deep Learning Research roles in the United States is fairly selective, failing a large portion of engineers who go through it.
Experience Rating
Candidates reported having mixed feelings for Nvidia's Applied Deep Learning Research interview process in United States.
Nvidia Work Experiences
- 5.0Sharp, Inclusive, Fast-pacedApplied Deep Learning Research • Current EmployeeSanta Clara, California, United StatesMay 30, 2017Pros: sharp colleagues, an inclusive and collaborative environment. Open to research ideas that might benefit NVIDIA in the 1-10 year interval. Even the 20 year GPU engineers are thinking in terms of deep learning applications.Cons: Everything moves fast. You should be used to the pace or have an adjustment period (2-3 weeks).
- 5.0Good pay, great work cultureASIC Design Engineer • Current EmployeeBengaluru, Karnataka, IndiaNovember 29, 2025Pros: Great work culture, supportive environment.Cons: Competition for growth due to a lot of strong and well-qualified colleagues.
- 5.0Great Pay, Tough EntrySoftware Engineer • Current EmployeeSanta Clara, California, United StatesNovember 28, 2025Pros: Really high-level base salary.Cons: Extremely competitive and hard to get into.
Nvidia Interview Questions
