Has anyone tried asking GPT-3 or one of its cousins?
How do you break into a career in machine learning? (2020)
21–30 of 64 posts
Re: How do you break into a career in machine learning? (2020)
#22I moved to a Machine Learning Engineer role a few years back. I just did an internal transfer to a ML team with no previous knowledge. The team trusted me to pick up whatever I needed on the job. Now I interview tons of people for MLE roles. Trying to get in "through the front door" is incredibly competitive. Not only you have to prove you are a great engineer, but also good ML knowledge. You'd be competing with peop…
> become and excellent engineer
Is there a reliable definition to that? A good balance between technical and communication skills or something among the lines?
Re: How do you break into a career in machine learning? (2020)
#23If you are in undergrad, I'd recommend something like, Math or math-heavy science BS -> undergrad research -> computationally heavy PhD -> entry level DS or ML engineer job -> senior ML job (within a year or two) If you are older and looking to pivot, I'd recommend, Data engineer -> senior data engineer -> entry level DS -> senior DS
> entry level job -> senior job (within a year or two)
Do words even mean anything anymore?
Re: How do you break into a career in machine learning? (2020)
#24I moved to a Machine Learning Engineer role a few years back. I just did an internal transfer to a ML team with no previous knowledge. The team trusted me to pick up whatever I needed on the job. Now I interview tons of people for MLE roles. Trying to get in "through the front door" is incredibly competitive. Not only you have to prove you are a great engineer, but also good ML knowledge. You'd be competing with peop…
Are these academic types great engineers? Do you find that the academics have a major edge in domain knowledge over self taught programmer?
Re: How do you break into a career in machine learning? (2020)
#25Funny there's no mention of ML without a PHD. Anyone done that?
I run several software teams that all have ML engineers on them, and two ML-specific teams of all ML engineers. Perhaps 14 ML engineers in total across my teams. We pay FAMGAN market rate. Their experience ranges from senior ML (6-8 years exp) to three who I hired right out of undergrad/masters, and two of those were interns who got job offers after internships.
Only one out of all of those have a PhD, and it’s only pseudo related. You absolutely do not need to have a PhD for 80% of positions in the modern world of ML in my experience, and I’d go as far as saying unless you want something significantly more prestigious than “market rate ML job doing interesting work” then a PhD is probably a net negative in life as an ML person given the opportunity cost. I have definitely turned down prestigious academia PhD types who wanted to move to industry in strong favor of strong SWEs with practical ML experience, and have a strong preference for same.
This definitely isn’t the answer academia or most people who have sunk cost of their time into PhDs would agree with, or necessarily like, but from a practical perspective it’s my experience across much of industry.
Re: How do you break into a career in machine learning? (2020)
#26If you are in undergrad, I'd recommend something like, Math or math-heavy science BS -> undergrad research -> computationally heavy PhD -> entry level DS or ML engineer job -> senior ML job (within a year or two) If you are older and looking to pivot, I'd recommend, Data engineer -> senior data engineer -> entry level DS -> senior DS
You don't need a PhD for DS/ML Engineer. Even at FAANG, even in their research labs. Usually a PhD is only in the requirements for Research Scientist (RS). That said, I did a PhD (and am now a RS). It's a fantastic opportunity to learn fully focused during a few years. But if your sole objective is the career (which is ok!), don't do a PhD. There are much easier ways to break into ML industry.
To add to this, companies at Google-scale tend to have a huge variety of ML related jobs, ranging from low level things like optimising libraries for different hardware, to the more general research positions where people are working on their own pet projects. Plus everything in between - data management and curation for training models that get used in production, people who try and figure out how to productionise cutting edge research, people who build the infrastructure that other ML engineers use (and here again, everything from hardware/server people, cloud, site reliability, tooling) and the list goes on.
I know of at least one person who got an ML job at Google, but didn't apply specifically for it. They had a very strong ML background and applied for a generic software engineering and got team matched. That seems like a reasonable way to go if you don't want to go through a research interview loop.
Re: How do you break into a career in machine learning? (2020)
#27Earlier quoted context omitted.
Into what?
I want to do backend development next, I find it much more interesting (and more rewarding to work on based on the things I've done).
This is literally opposite of me. Would you mind elaborating a bit on the negatives of working on the ML side of things?
Definitely not saying your wrong or that it's better than backend dev (it's probably just personal preference). But as someone considering it, I'd like to hear the good and bad of each type of role.
Re: How do you break into a career in machine learning? (2020)
#28Funny there's no mention of ML without a PHD. Anyone done that?
The attitude that you need a PhD to practice ML is over a half-decade old.
Modern ML tooling has progressed enough that not only is a PhD not necessary, but overcomplicating ML model construction fully utilizing said PhD can easily lead to technical debt and make things worse.
Re: How do you break into a career in machine learning? (2020)
#29MLOps is a good way for someone with a Cloud Engineering or DevOps skills set to join a team and start learning from within
In my experience no matter the field breaking into it via ops is almost a certain way to never get to where you want to be. Cloud Engineering/SRE/MLOps are so in demand a company would be foolish to let you move up unless you really, really made a stink about it.
Better to just get your MSc in statistics/CS. It's possible to break into the field with less but of the (very talented) ML engineers/scientists I know the ones with the BScs are basically stuck. Most people want to actually make cool models and novel ideas. You won't get to this position without an MSc /PhD.
Re: How do you break into a career in machine learning? (2020)
#30I moved to a Machine Learning Engineer role a few years back. I just did an internal transfer to a ML team with no previous knowledge. The team trusted me to pick up whatever I needed on the job. Now I interview tons of people for MLE roles. Trying to get in "through the front door" is incredibly competitive. Not only you have to prove you are a great engineer, but also good ML knowledge. You'd be competing with peop…
Are these academic types great engineers? Do you find that the academics have a major edge in domain knowledge over self taught programmer?
You're not really an academic unless you're working in the academy, right? Once you move to industry, you're a professional.