Hey Jan! Just discovered your channel and really appreciate your videos and your perspective. I am also an Electrical Engineer and just finished my PhD. I am hoping to get a job at a big tech company like Google or Apple. Unfortunately, I didn't have enough foresight to intern at big tech companies, and instead just focused on my PhD research during summers. However, I did work as a firmware engineer writing code in the C programming language at a medium-sized semiconductor equipment company for 4 years before I started grad school, so I have some industrial experience. Do you have any advice/tips on how I could get a position at Google/Apple?
@@zabava3248 I haven't been able to get a job at a big tech / FAANG company yet. The economy is really tough right now in tech. If I was to redo my PhD I would probably focus on Machine Learning / Artificial Intelligence or Robotics since those seem to be the couple of bright spots that tech companies are really investing in right now and still hiring for.
This is a great videos. The AI/ML startup space is growing rapidly in the past decade and I'm sure many people will find this video useful. I appreciate the captions as well. Two follow-up questions I have is the fact that you mentioned that you went to work at a startup immediately after graduating from grad school. I know that many people recommend switching jobs every couple of years (within reason) to get substantially better pay increases than if one had just remained at one job for the entire time. Do you think that intentionally targeting working at a startup that you don't intend on working at for a long time after graduating grad school, and then leaving after a few years to pursue jobs that you actually do want to do so that you can get a pay increase at those bigger jobs as opposed to what you would've gotten if you went to those bigger companies right after graduation is a valid strategy? What are the pros and cons? The other question I have is regarding the things you learn while working at a startup. Working at a startup makes you have to learn a lot of things on your own and be more self-sufficient than you would be at a bigger company with a better support network and more team members. Does working at a startup teach you more skills to the point that you would not have learned as much if you had gone directly to a Google/Microsoft company after graduating? Thereby making you more employable in the long run?
Good questions! I was not strategic about going to a startup, but I wish I was. I definitely didn't take the job thinking I'd leave after 2 years. At the time, before I started and for maybe the first year or so, I was actually thinking I'd be there for a while. I think I could have stayed a couple more years and grown professionally, maybe even leveled up, a lot faster, but there were a lot of reasons I didn't want to stay. If the culture is really good, I think I'd rather work at a startup and grow with it, as opposed to working at a large company, but my team and the team's culture are a couple of the most important things either keeping me at a company or pushing me out. I also do not think I would have learned as much as I did in my 2 years at the startup if I had gone to Google right away. I wish I could've stayed a bit longer, because I felt like I was learning and growing very quickly, so I do think going to the startup helped me a lot, but I don't think I stayed long enough to reap all the benefits. I think 'the long run' is hard to consider, because (IMO) whatever you're doing *right now* is most important for what you'll be doing next. Meaning, like, if I switch jobs again, hiring managers/recruiters are going to place a lot more weight on what I'm doing currently to represent my skillset/interest and less weight on my startup experience. My startup experience helped me get my current position, and my current position will help me get my next one (if there is one 😏). Who am I to say though? I've only been working in industry for a few years, so maybe I’ll think differently if you ask again in another few years😅
Can you expand on your pivot into SWE after investing so much time into EE? As someone with a similar opportunity, I would be interested to hear what motivated you.
I recently had an interview at an AI start-up and their first question was, "Are you prepared to work 'hardcore' hours?" And I was totally put off and ended the interview pretty quickly after that. I have from then on sort of avoided applying to start-ups because I thought their teams seemed inexperienced (which you sort of touched on re challenge #5) but also have an unhealthy work-life balance culture. Do you find there are big cultural differences between the 'big tech' and 'small tech'/start-up companies?
Oh gosh. 'Are you prepared to work hardcore hours?' is not how I'd ask it 😅, but when I was at the startup and interviewing people, I'd try to get a sense for what their worth ethic is like through my questioning, seeing what questions they ask, and by talking about the company culture and seeing how they respond. Sometimes they'd ask directly what the work-life balance was like, and I had to be honest - I was working probably, on average, ~65-hour weeks. I think some people wanted to grind and were ready to work a lot (usually younger people, like me when I took the job 🥺), but it quickly gets exhausting, and I found it unsustainable. In my experience, the cultural differences between bigger companies and startups has a lot of similarities (mostly with politics and bureaucracy), but work-life balance, specifically, is night and day. Also, I think at larger companies, the culture and WLB is determined more by the team, so the experiences in 'big tech' will likely vary quite a bit depending on who you ask.
@@janpancake Thanks! Really insightful. Possibly start-ups won't be a good fit if that's a common theme. Although, good to know that work-life balance can vary a lot team-to-team in larger companies :)
This really inspired me. I just completed my bachelors in Electrical(Power Systems)Engineering and i'd like to forward into AI. Can you give a roadmap? Should I get a masters straight on or take some courses first? Thanks Jan.
If you don't have AI experience, I'd say yes to going for the MS. It can give you the foundation you need to get an internship or first job in AI. I think it's much harder to start working as an EE at a company that does AI and switching within the company later (with or without having taken ML classes). I know people who have switched roles/teams in companies from non-ML-related roles to ML roles without ML experience, but it's pretty rare. Hope this helps!
Im pursuing my bachelor's degree in supply chain, transportation, and logistics management. How can I get into machine learning from a supply chain perspective. Thanks in advance
Interesting question - I honestly am not sure, but from a quick Google search, I can see that there are supply chain/logistics problems that people are currently trying to solve with ML. If you don't go to grad school and try to get into ML that way, you could try to get a job at a company trying to solve supply chain problems with ML (e.g., ML for inventory management). Another related area worth exploring is possibly data science if you want to gradually move toward ML. I hope this helps, and good luck!
Thanks! I really enjoy all of your videos and how insightful and honest you are.
Very good points! Keep up the good work
Hey Jan! Just discovered your channel and really appreciate your videos and your perspective. I am also an Electrical Engineer and just finished my PhD. I am hoping to get a job at a big tech company like Google or Apple. Unfortunately, I didn't have enough foresight to intern at big tech companies, and instead just focused on my PhD research during summers. However, I did work as a firmware engineer writing code in the C programming language at a medium-sized semiconductor equipment company for 4 years before I started grad school, so I have some industrial experience. Do you have any advice/tips on how I could get a position at Google/Apple?
Hey,Hows your journey so far, Im also an EE major interest in my phd.
@@zabava3248 I haven't been able to get a job at a big tech / FAANG company yet. The economy is really tough right now in tech. If I was to redo my PhD I would probably focus on Machine Learning / Artificial Intelligence or Robotics since those seem to be the couple of bright spots that tech companies are really investing in right now and still hiring for.
This is a great videos. The AI/ML startup space is growing rapidly in the past decade and I'm sure many people will find this video useful. I appreciate the captions as well.
Two follow-up questions I have is the fact that you mentioned that you went to work at a startup immediately after graduating from grad school. I know that many people recommend switching jobs every couple of years (within reason) to get substantially better pay increases than if one had just remained at one job for the entire time. Do you think that intentionally targeting working at a startup that you don't intend on working at for a long time after graduating grad school, and then leaving after a few years to pursue jobs that you actually do want to do so that you can get a pay increase at those bigger jobs as opposed to what you would've gotten if you went to those bigger companies right after graduation is a valid strategy? What are the pros and cons?
The other question I have is regarding the things you learn while working at a startup. Working at a startup makes you have to learn a lot of things on your own and be more self-sufficient than you would be at a bigger company with a better support network and more team members. Does working at a startup teach you more skills to the point that you would not have learned as much if you had gone directly to a Google/Microsoft company after graduating? Thereby making you more employable in the long run?
Good questions! I was not strategic about going to a startup, but I wish I was. I definitely didn't take the job thinking I'd leave after 2 years. At the time, before I started and for maybe the first year or so, I was actually thinking I'd be there for a while. I think I could have stayed a couple more years and grown professionally, maybe even leveled up, a lot faster, but there were a lot of reasons I didn't want to stay. If the culture is really good, I think I'd rather work at a startup and grow with it, as opposed to working at a large company, but my team and the team's culture are a couple of the most important things either keeping me at a company or pushing me out.
I also do not think I would have learned as much as I did in my 2 years at the startup if I had gone to Google right away. I wish I could've stayed a bit longer, because I felt like I was learning and growing very quickly, so I do think going to the startup helped me a lot, but I don't think I stayed long enough to reap all the benefits. I think 'the long run' is hard to consider, because (IMO) whatever you're doing *right now* is most important for what you'll be doing next. Meaning, like, if I switch jobs again, hiring managers/recruiters are going to place a lot more weight on what I'm doing currently to represent my skillset/interest and less weight on my startup experience. My startup experience helped me get my current position, and my current position will help me get my next one (if there is one 😏).
Who am I to say though? I've only been working in industry for a few years, so maybe I’ll think differently if you ask again in another few years😅
Can you expand on your pivot into SWE after investing so much time into EE? As someone with a similar opportunity, I would be interested to hear what motivated you.
I recently had an interview at an AI start-up and their first question was, "Are you prepared to work 'hardcore' hours?" And I was totally put off and ended the interview pretty quickly after that. I have from then on sort of avoided applying to start-ups because I thought their teams seemed inexperienced (which you sort of touched on re challenge #5) but also have an unhealthy work-life balance culture. Do you find there are big cultural differences between the 'big tech' and 'small tech'/start-up companies?
Oh gosh. 'Are you prepared to work hardcore hours?' is not how I'd ask it 😅, but when I was at the startup and interviewing people, I'd try to get a sense for what their worth ethic is like through my questioning, seeing what questions they ask, and by talking about the company culture and seeing how they respond. Sometimes they'd ask directly what the work-life balance was like, and I had to be honest - I was working probably, on average, ~65-hour weeks. I think some people wanted to grind and were ready to work a lot (usually younger people, like me when I took the job 🥺), but it quickly gets exhausting, and I found it unsustainable. In my experience, the cultural differences between bigger companies and startups has a lot of similarities (mostly with politics and bureaucracy), but work-life balance, specifically, is night and day. Also, I think at larger companies, the culture and WLB is determined more by the team, so the experiences in 'big tech' will likely vary quite a bit depending on who you ask.
@@janpancake Thanks! Really insightful. Possibly start-ups won't be a good fit if that's a common theme. Although, good to know that work-life balance can vary a lot team-to-team in larger companies :)
This really inspired me. I just completed my bachelors in Electrical(Power Systems)Engineering and i'd like to forward into AI. Can you give a roadmap? Should I get a masters straight on or take some courses first? Thanks Jan.
If you don't have AI experience, I'd say yes to going for the MS. It can give you the foundation you need to get an internship or first job in AI. I think it's much harder to start working as an EE at a company that does AI and switching within the company later (with or without having taken ML classes). I know people who have switched roles/teams in companies from non-ML-related roles to ML roles without ML experience, but it's pretty rare. Hope this helps!
Hiiiiii Janice !!!! How have you been? I missed you so much :(
Missed you too 🥰
Im pursuing my bachelor's degree in supply chain, transportation, and logistics management. How can I get into machine learning from a supply chain perspective. Thanks in advance
Interesting question - I honestly am not sure, but from a quick Google search, I can see that there are supply chain/logistics problems that people are currently trying to solve with ML. If you don't go to grad school and try to get into ML that way, you could try to get a job at a company trying to solve supply chain problems with ML (e.g., ML for inventory management). Another related area worth exploring is possibly data science if you want to gradually move toward ML. I hope this helps, and good luck!
How did you manage your student loans during grad school?
Mam how much do you earn now? Plz reply. Thanks a lot.