A real engineering company with access to technology that is rarely found elsewhere. Optics, electronics, precision motion systems, high speed image computers, robotics, complex system software, and difficult optimization problems
K-T provides access to all those technologies at one company.
Growth has slowed and opportunities and compensation have slowed with it. It's a semiconductor company and this segment has always been cyclical. Expect lots of ups and downs and some job insecurity in the down cycles.
In the next cycle find a growth opportunity that is outside of the semiconductor area and figure out how to make is a reality.
Two phone screens, one full-day onsite with 5 people. People were nice. General discussion on background work. etc. Like most other interviews, maybe not as intense. It is a semi-formal place so maybe you can get away with jeans and t-shirt, but ad
A phone interview and then they flew me in for a presentation and a series of eight 1-on-1s. In this series of 1:1s, lots of questions come over and over and make it boring. In addition, every interviewer tends to ask questions about his own backgro
2 rounds both focusing on ML questions, mostly focused on resume. The second round was with hiring manager and also included a LeetCode question which at a medium level. The ML questions were focused on GANs, learning rate schedulers etc.
Two phone screens, one full-day onsite with 5 people. People were nice. General discussion on background work. etc. Like most other interviews, maybe not as intense. It is a semi-formal place so maybe you can get away with jeans and t-shirt, but ad
A phone interview and then they flew me in for a presentation and a series of eight 1-on-1s. In this series of 1:1s, lots of questions come over and over and make it boring. In addition, every interviewer tends to ask questions about his own backgro
2 rounds both focusing on ML questions, mostly focused on resume. The second round was with hiring manager and also included a LeetCode question which at a medium level. The ML questions were focused on GANs, learning rate schedulers etc.