Can I get a job at Google in AI/ML?
Be good at what you do, and people will start taking notice. I’ve often come across questions where people tend to gravitate more towards seeking job opportunities at prestigious companies, research institutes or Universities. According to me (and it’s a completely personal opinion), the motivation to study machine learning, deep leaning or any other other field just for the sake of getting a good job at Google or Microsoft is not enough rather you should aim at becoming so good at your respective domain that people at these giant companies start taking notice, and the only way to do this is to enjoy what you do.
- The moment you enjoy machine learning, you will start exploring all the subdomains within it.
- You will start reading the latest papers appearing in the archive.
- You will start contributing to the various open-source libraries like PyTorch, Keras etc.
- You will start reading blogs by machine learning giants like @Andrej Karpathy, @Chris Olah and various other ML enthusiasts on platforms like Medium — Read, write and share stories that matter or distil.pub
- You will start taking part in various data science completions hosted in Your Home for Data Science.
- You will eventually start writing your own blogs, explaining the various intricacies involved in different ML algorithms for the benefit of your readers.
The point is, when you start doing the above-mentioned things, you will develop a passion for ML. Getting a job at Google or Microsoft will be secondary to you. You will start exploring the horizons of ML and DL because you really want to learn and not for the purpose of securing a job.
When this happens your profile at LinkedIn will speak tonnes about your work and it will surely fall in the eyes of recruiters from these tech giants. It will be they who will contact you not the other way round. At the end of the day, you will undoubtedly have multiple offers at your hands and it will be you who will negotiate your salary with them.
So my advice to you is sharpen your skills, clear your concepts, start to fall in love with statistics and probability, always lookout for ways to contribute in open source projects. Make Github your facebook. Follow people who contribute a lot in the domain of ML and DL, observe the way they code, learn from them.
In conclusion, I’ll say you can start learning at
New Machine Learning Project Course for Beginners
hope you got your answer