What do ML engineers do on a day to day basis?
Any ML/AI engineer who can share, what does a day to day work look like for you ? Is it mostly a research based role ? Do you code regularly ?
Hey everyone, happy to answer any questions around Data Science/ML/AI and making a career within it
A brief about me, I work currently as a Sr. ML Engineer at an Indian unicorn startup I graduated 5+ years ago and have since worked as a Data Scientist / ML Engineer at an ecommerce company and social media company. My designations have changed based on the industry requirements and work too changed based on that.
Would love to take questions on what it means to be an ML Engineer, my early learnings from a career in data science, and thoughts on AI.
Look forward to all questions :)
A simple exploration on growws mutual fund comparison reveals quant active and even quant tax plan have consistently outperformed parag Parikh by a long margin
thanks for doing AMA,
With seniority, part of my day goes into meetings - discussions around what is it that we are building, progress checks, brainstorming around what to build next, PRD etc. I also have the added on responsibility of a team lead, where I have to delegate work and ensure timelines are met - in other words - do standups and unblock people. I try to dedicate the rest of the time for coding purposes. Some days hacking things together in a jupyter notebook, other times deploying some change, some days integrating the ML stuff with our backends.
Again, not many people have the role I do, where I have to and can make contributions to model building, production deployment and planning. So the above stuff varies for others around me where some do more hardcore model building & analysis
On question 2,
Gen AI is truly a game changer, ChatGPT, Copilot & the likes enable everyone to ship faster. Designers around me use the Adobe beta image gen functions for their work. I have seen some backend folks generate code from tools like locify from a figma mockup.
Rewording one of the popular sentiments around the recent developments - Gen AI enables the experts to be more efficient.
How do you manage to stay upto date on the new emerging technologies and updates in the filed ? Asking as I'm currently facing that issue as a fresher(1yoe))
Twitter!! I can share later the accounts you have to follow to be uptodate. But that's the only platform you have to be on to be aware of what is happening.
Please share the accounts links
As a fresher graduating from college, preparing for ML roles, what specific areas should one focus on especially to crack an interview?
And how does does DSA play a role in interview?
Strangely DSA is something that is never ever useful but rated super highly in your interviews. I would recommend for freshers to continue the leetcode bullshit, and build side projects around to showcase your ML capabilities. Get on twitter and start getting inspired by indie developers hacking things together.
Any company looking at your online work would love to have you, as this separates you from the 1000s of others who also "want" to do AI and fancy shit
Ah thats a bit sad...This screening is very worthless I feel and considering the ongoing internships in hand(ML intern @Siemens, AI Product intern at a Startup) it becomes difficult to practice DSA(and frankly I don't like it I'd rather want to experiment with a new model). I've even won Smart India Hackathon'22 and also participated in many other hackathons have other hands on experiences too but just the notion that you've to go through that DSA round despite dev skills crushes me. Can't complain much , have to learn it the hard way :(
Still hopeful and working hard 💪
Thankyou.
How much value do you think a masters/PhD would hold in the space. I've been working in the space for a couple of years and am a little confused on how to proceed
I personally would do what Thiel does as soon as I get that rich. Which is to sponsor people to drop out from the colleges/universities. Because they are truly waste of your time if your ambition or goal is something else / bigger.
By goal - if your goal is to do heavy research then yes, phd & masters is the way, you can get yourself into google and the likes and get something massive out. But if your goal is to be the data scientist at udaan, I don't think you need masters or phd for that
Having said that I can see why an employer would prefer a masters & phd candidate over a undergrad with some experience.
What if the person wants to get the international exposure but can't due to not being from tier 1&2 colleges
Any ML/AI engineer who can share, what does a day to day work look like for you ? Is it mostly a research based role ? Do you code regularly ?
Hey everyone, excited to be doing this AMA!
A brief about me, I work currently as a Director of Product at an Indian unicorn startup
About my career:
I recently started working as a Data Analyst after my undergraduate in Engineering. My work concerns mostly building, testing and tracking ML models for Finance Industry (usually classic ML and not Deep Learning).
I wanted to hear from...
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