257 karma · joined March 2, 2009
There are 3 common cases of when the paperwork is filed. First, foreign students who graduated from American universities in certain fields can work for a certain period of time after which they can transition to H-1B. So the salary is pretty much what they are paid when the application was filed which is somewhere between 1 and 27 months. Second, people hired from overseas or within the US who aren't new graduates and don't have a current H-1B visa. Their salary would be what the company offered to get the talent. The third case is when you transfer you H-1B visa where an application is not required so there is no change to the salary in the application.
A major problem with Glassdoor salaries is the absence of a date range. The salaries they show is the average over the period of time starting when they started collecting salaries. So yes the salaries on Glassdoor tend to be lower than the current average.
A lot (too many) people on HN are claiming $200k base salary per year as being totally normal.
I agree. It is pretty high. My own reference for base salaries is my own website where I collect H-1B salaries. We also have an option to only show the salary distribution starting on a given year. For instance, for a software engineer at FB, the average base salary is $149k if you only include salaries reported after 2015 [1]. At Netflix however, Sr. Software Engineers make $200k on average[2].
[1] http://h1bpay.com/companies/Facebook/cities/Menlo%20Park-CA/...
[2] http://h1bpay.com/companies/Netflix/cities/Los%20Gatos-CA/jo...
Basically, only Microsoft is among the top 10 sponsors and not of the major sponsors is among the top 10 average salaries.
Second, I registered for the Machine Learning course (I am not sure if the same applies to the AI course) and I compared it with the actual ML course at Stanford (CS229) (I mainly looked at Youtube videos of Andrew[1] as well as Assignments/Midterm[2]). The latter is by far more advanced and theoretical. The assignments tend to test more than basic comprehension of the material presented in the lectures, which is exactly what the online course reviews tend to evaluate. They require strong mathematical knowledge and obviously a minimum level of creativity/intelligence.
[1] http://www.youtube.com/results?search_query=machine+learning...