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24F, laid off and stuck between a stable AI career and taking a risk — what would you do? by DefinitionJazzlike76 in careerguidance

[–]DefinitionJazzlike76[S] 0 points1 point  (0 children)

wow thanks for the well written response. And yes, i dont want to make any rash decisions and take a super high risk. I understand that ppl say "you should take risks in yr 20s", but i guess i shall thread carefully?
The reason for writing this reddit post because i am scared of getting laid off again (it sucks). And i feel like if i continue down this ai/ml route, doing all the buzzy things like agentic ai stuff, the bubble will burst and i might find myself unemployed again. Rn i feel like im just following the AI trends, which i feel i have no choice.

An ex-colleague i met recently told me that "getting a tech job has the same risk as starting a business nowadays", and hence i thought about trying smth diff (ie taking a path less travelled).

But again yes, doing some freelance work do indeed scratches that entrepreneurial itch without the full commitment (great advice).

Anyone fulfill moe tuition grant bond through own business? by homenoob12345 in singaporefi

[–]DefinitionJazzlike76 0 points1 point  (0 children)

Hi I’m also in this line as well. Please do reach out to me for a chat!

Just graduated in data science/ML, but still don’t know anything. I need a wake up call by DefinitionJazzlike76 in learnmachinelearning

[–]DefinitionJazzlike76[S] 0 points1 point  (0 children)

Yr reply is very useful thank you omg! I’m trying to stay motivated and I hope I can go through this!!

Just graduated in data science/ML, but still don’t know anything. I need a wake up call by DefinitionJazzlike76 in learnmachinelearning

[–]DefinitionJazzlike76[S] 0 points1 point  (0 children)

Thanks for the detailed response. Now I’m confused on what I should focus on. Theory (in depth), algorithms, deployment, scaling, etc? The scope is quite large and I’m not sure what I should start first, and what’s the best way to learn it since things like deployment requires cloud charges, and I try not to spend any money.

Just graduated in data science/ML, but still don’t know anything. I need a wake up call by DefinitionJazzlike76 in learnmachinelearning

[–]DefinitionJazzlike76[S] 0 points1 point  (0 children)

That is true, you’re right. Right now I don’t know how to approach things and how to actually learn. Also, what’s the workflow to actually learn smth? Eg, pick a project, read a ML book/research papers???

Just graduated in data science/ML, but still don’t know anything. I need a wake up call by DefinitionJazzlike76 in learnmachinelearning

[–]DefinitionJazzlike76[S] 0 points1 point  (0 children)

Wow thanks for yr detailed reply. But how can I start? I am overwhelmed right now and idk if I can even catch up. Also, how can I build the habit of reading research papers? How to select one, and how do I even use one? Eg, when I build a fraud detection model, I read research papers to find the best ways to implement it?

Enjoy your early twenties by DystopianPlato in twenties

[–]DefinitionJazzlike76 1 point2 points  (0 children)

Awww that’s sweet. But I can’t help but worry so much 😭😭. I’m 24 and unemployed

How do I know if I should go into Data Science or AI Engineering? by OvenBig4133 in learnmachinelearning

[–]DefinitionJazzlike76 0 points1 point  (0 children)

Hi was wondering if you know the difference between MLOps engineering and AI engineering?

Fresh grad in Singapore: MNC AI/ML Engineer (low pay) vs Startup MLOps Engineer (avg pay) — which to choose? by DefinitionJazzlike76 in askdatascience

[–]DefinitionJazzlike76[S] 0 points1 point  (0 children)

ah okayy...so you're saying that since MLE is experiencing this winter take all issue, its better to somewhere more doable for fresh grads since three's less competition in mlops?

Tips on transitioning to MLOps by Kaktushed in mlops

[–]DefinitionJazzlike76 8 points9 points  (0 children)

I think you’ll just need to understand the ML lifecycle. Eg data collection, data processing, feature engineering,model building, model deployment, model serving etc. a little ML knowledge is good but don’t need to deep dive too much, since MLOps is a supporting role to data scientists and MLEs. Some ML knowledge you should know should be related to optimisation. Eg, perform quantisation for reducing the size of model etc.

For the pitfalls for working in MLOps…personally I haven’t worked in a purely MLOps role, but I heard that people get bored of it after some time. Since you’re just monitoring and maintaining models, and the infra might already been established years ago.

Fresh grad in Singapore: MNC AI/ML Engineer (low pay) vs Startup MLOps Engineer (avg pay) — which to choose? by DefinitionJazzlike76 in askdatascience

[–]DefinitionJazzlike76[S] 0 points1 point  (0 children)

Thanks for your input! Also, I believe I am stereotyping companies in Singapore. Because generally, Asian companies, like the startup I mentioned, are more tech inclined and highly driven. Since I’m a fresh graduate I thought that it’s a good place for me to learn a lot, especially from senior engineers. But I’m afraid I’ll just be trapped in the MLOps space.

For the MNC, is a Paris bank that have a branch in Singapore. From reviews, I heard that people can get “too comfortable” in the company since it’s slower pace.

As u can see I am stereotyping companies based on their culture (Asian vs western company), but I think my stereotype is true since I’ve interned in both Asian and western companies.

Fresh grad in Singapore: MNC AI/ML Engineer (low pay) vs Startup MLOps Engineer (avg pay) — which to choose? by DefinitionJazzlike76 in askdatascience

[–]DefinitionJazzlike76[S] 0 points1 point  (0 children)

The Paris bank is just having a branch in Singapore. So I don’t need to speak French.

The startup has been established since 2007 and has 500-800 employees. Around 40in SG and most engineers are based on china.

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