r/AIMLDiscussion

So basically i am from healthcare background with almost 12 years of experience, currently in manager role. Off late with all the fuzz around AI i have this FOMO, so should i start learning ?? I mean as a non tech person can i do it ? I did had conversation with scaler team as well but it too expensive and course time was also lengthy restricted to only weekends. So people in tech AI i want to understand your first hand opinion it worth the effort and time?? I basically work in PV and there are few areas where there is automation happening but considering highly regulated industry i don’t there will be drastic changes. Please provide your suggestions.

I want to share this because I’m sure I’m not the only person who has gone through this.
I’m 23, from Argentina, and over the last few months I’ve been trying to find a way into the AI industry.
Not as an AI engineer. Not as a machine learning expert.
I was looking for entry-level opportunities where I could actually use my skills: AI evaluation, data annotation, content, training AI models, and similar work.
At first, I thought it would be relatively easy.
I use ChatGPT and Claude a lot. I have experience with marketing, social media and content creation, and I’ve spent a lot of time learning how AI tools work.
So I thought: why not try?
That was when the rabbit hole started.
I signed up for Outlier and Remotasks, but I kept running into redirects, unavailable projects and access problems. I would complete my profile, look for work, and then… nothing.
Then I tried Prolific.
That didn’t go very well either. At one point I couldn’t even properly access my account and got the message:
“PEC-GL-0003: User not found.”
Which was honestly pretty frustrating after spending time trying to get everything set up.
I also tried Claru.ai, Data2Sales AI, HumanSignal, YPAI, Kled.ai and Atlas Core.
Some of them didn’t have projects available. Some had registration or access issues. In other cases, I simply couldn’t get past the point of actually finding work.
And after doing this over and over, I started asking myself:
“Am I doing something wrong?”
Because online, you see people talking about AI jobs all the time.
You see posts saying things like:
“Earn money training AI.”
“Work remotely.”
“Become an AI trainer.”
It sounds incredibly accessible.
But when you actually try to do it, you discover that getting the opportunity can be the hardest part.
And then there was Mindrift.
That was the first platform where I actually managed to move forward.
It wasn’t some huge breakthrough where suddenly everything worked perfectly.
But it was enough to make me realize:
Maybe I can actually find a place in this industry.
The interesting part is that my background isn’t really technical.
I’m from Argentina.
My native language is Spanish.
My English is still something I’m working on. I can understand and communicate in English, but I’m definitely not at a native or advanced professional level yet.
And honestly, that has made this whole process more difficult.
A lot of the information, communities, documentation and opportunities are in English.
So now I’m at a point where I don’t want to keep randomly signing up for every AI platform I find.
I want to actually learn.
I want to understand what I’m doing and build skills that companies are looking for.
I’m interested in AI evaluation, LLMs, data annotation, prompt engineering, computer vision, dataset creation, Python and, of course, improving my English.
But I have a problem:
I don’t really know where I should start.
So I’m posting this hoping someone with more experience can point me in the right direction.
If you’ve worked in AI training, data annotation, AI evaluation or anything similar:
What would you recommend learning first?
Are there courses or certifications that are actually worth doing?
Are there communities where beginners can learn and ask questions?
Which platforms are genuinely worth trying in 2026?
And most importantly, what would you recommend to someone like me?
A 23-year-old from Argentina, native Spanish speaker, still improving his English, with experience in marketing and content, who wants to seriously get into AI.
I’m not looking for a shortcut anymore.
I just want to find the right path.
I’ve already tried a lot of doors.
Most of them didn’t open.
But one finally did.
Now I want to know what I should do with that opportunity.
If you’ve been through something similar, I’d really appreciate your advice.
I’m still at the beginning of this journey, but I don’t want to give up.
Maybe someone reading this was in the exact same position at some point.
If that’s you, I’d love to hear your story.
#AI #ArtificialIntelligence #AITraining #DataAnnotation #AIEvaluation #LLM #CareerInAI #RemoteWork #Argentina #LearnAI #Mindrift

I have some experience in AI engineering, even though right now I am working in a different field, which is automated QA software testing. I have created some AI products before, mainly chatbots, but I feel like I have lost touch, given my job has consumed a bit of my time that I would have used to learn the latest trends. I want to go dive back into the AI space, but it is very difficult for me to find one now due to uncertainty in the niche I'd want to pursue, as well as competing with PhD and master's holders. I enjoy coding, and I want to apply my skills on a production level, but I am unsure as to how to proceed. Like, yes, I can build and deploy chatbots, though I want to try something more technical in the sense that it can make me stand out more from other AI engineers? I have always wanted to try AI with robotics, but I need to pay my bills, and in the country where I am situated, we don't have jobs like that here. I want to do something more technical and challenging, given I enjoy learning new things, but I am unsure how best to proceed. I am aware there are roles like MLOps, Forward Deployed AI Engineers (which is a role I just learnt exists recently), LLMOps, AI Systems Engineers, etc., but from what some of you guys are doing, which path did you take? Also, how challenging is your role, and is it something you might say might be the least likely to be automated by AI? Finally, do I need to pursue a master's for it?

ML Roles OA — What to Prepare?

Hi everyone! I’m preparing for ML/AI roles and wanted to know what is generally asked in OAs.

For those who have recently appeared for ML roles:

- Where can I find previous ML OA questions/experiences?

- What ML topics are commonly asked?

- How much DSA/coding is asked, and what difficulty?

- Is Python acceptable for DSA, or is C++ preferred?

- How much do ML projects matter in the hiring process/interviews?

Any resources or recent experiences would be really helpful. Thanks!

I am a 4th semester CSE student at BMSIT Bangalore, entering 5th sem. Honestly, I feel like I've explored too many things without actually getting good at any of them.

I've done a little DSA, very little web development (i.e HTML/CSS), some ML/AI, and I'm currently learning FastAPI. I'm interested in Al and I also have a pretty strong mathematical background/intuition, but right now everything feels scattered and incomplete. I don't have any serious projects or a strong portfolio either.

I want to seriously fix this now. I'm willing to put in 200% over the next 12-18 months. My immediate goal is to get a good internship by the end of 5th sem and eventually become an Al Engineer with a good salary.

I also have an education loan and very little financial support, so I can't really afford to spend years randomly trying different technologies.

If someone experienced in Al/ML hiring or someone who has gone through a similar journey could guide me, I'd really appreciate it.

If you were in my exact position, what would you do from Day 1 of 5th sem? What would you prioritize between DSA, backend/SWE, ML, deep learning, GenAl, projects and deployment? What would you completely ignore?

And most importantly, what actually gets a Tier-3 student an Al/ML internship?

I'm looking for a practical advice. If you had 6 months to make yourself genuinely employable from my position, how would you spend those 6 months?

28 with a 3-year career gap — trying to transition into AI Engineering. Need honest advice
I’m 28 with a 3-year career gap. I previously worked for 2 years at Bank of America in automation testing, and before that as a mechanical engineer.there were several personal problems broke me apart and so the gaps had to happened I’m not saying this as an excuse. I take responsibility for losing consistency and letting the gap grow.

I’ve decided to transition into AI/GenAI engineering and have been learning for around a year.

I’ve built projects around RAG and Agentic AI, and RAG is currently my strongest area. I’ve worked with:
RAG, chunking, embeddings, FAISS, Chroma, Qdrant, PGVector, BM25, hybrid search, MMR, reranking, query transformation, HyDE, LangChain, LangGraph, Agentic RAG, LangSmith, RAGAS, FastAPI, Docker.
My biggest weakness is coding. I know Python but I’m not yet at the level where I can confidently build systems from scratch without relying heavily on documentation/AI.
I’m trying to avoid endlessly jumping between frameworks and actually become employable.
For people currently working in AI/ML/GenAI:
How would you approach Python/coding proficiency?
LeetCode/DSA vs projects vs backend development?
What skills are actually essential for an AI Engineer?
What would you stop learning?
How would you structure the next 6–12 months?
And realistically, is a 28-year-old with a 3-year gap and previous automation experience still capable of breaking into this field?
I’m not looking for motivation or sympathy. I want honest criticism and a practical roadmap.

Im confused if I should study cybersecurity or go with AI/ML. How is the current job market? to the people who are actively working in this field, id be really happy if you could share your experiences for all the folks with similar doubts. How do you think the market will look like 5-6 years later?
Im a student from india but any kind of advice is helpful regardless of the region.

Are there any suitable alternatives for me? which are similar to these fields?
Thank you and have a nice day :)

Hello everyone,
I’m a recent 2026 graduate from a Tier-3 college, and getting good placement opportunities has been really difficult. Because of that, I decided to pursue the online **BS in Data Science and Applications from IIT Madras** alongside my career journey, mainly because I wanted to learn from strong professors and also explore better opportunities through the program.
Over the past year, I’ve spent most of my time seriously learning and building my skills. I’ve worked through the fundamentals of **Machine Learning, mathematics, statistics, Python, and data science**, and then moved into **Deep Learning with PyTorch**. More recently, I’ve been learning **Generative AI, Transformers, RAG, LangChain, and related LLM technologies**.
I genuinely enjoy AI/ML and have been trying to build my career in this field.
However, because of my family situation, pursuing a full-time Master’s degree isn’t financially practical for me right now. I need to start earning and support my family.
Recently, I received an opportunity as a **Software QA/Automation Engineer**. The role comes with around 6 months of training/internship followed by FTE, but there is also a **2.6-year bond**. I accepted the offer because, at that point, I didn’t really have another option and I needed a job.
But after joining, I’ve started questioning whether I’m moving in the right direction. My long-term goal is AI/ML, and I’m worried that spending the next few years in a testing/automation role will make it even harder for me to transition into AI/ML later.
I’ve reached out to many people on LinkedIn asking for advice, guidance, or opportunities, but unfortunately I haven’t been able to find much help so far.
I’m seriously looking for a way to transition into **AI/ML/Data Science/GenAI roles**, even if it means starting from an entry-level position and proving myself through my work.
If anyone here is:
Hiring freshers for AI/ML, Data Science, or GenAI roles
Willing to provide a referral
Has successfully transitioned from QA/automation/software roles into AI/ML
Can guide me on what skills or technologies I should focus on
Can suggest good projects, open-source contributions, internships, or platforms where I can gain real-world experience
…I would genuinely appreciate your advice.
I’m not looking for shortcuts. I’m willing to put in the work and learn whatever is required. I just need some direction and hopefully an opportunity to prove myself.
If you’ve read this far, **thank you sincerely**. Even a small piece of advice, a referral, or pointing me in the right direction could make a huge difference for me right now. 🥹
Thank you everyone.

Hi all, I'm writing a blog post on how new grads or current software engineers can transition into AI engineering and the main thing I'm focusing on is production AI engineering.

There are a lot of people who have been trying to work on AI projects but they are very far from being production-grade. All they do is maybe connect a few APIs with each other, build a UI for it, and call it a day but there's a lot more that goes into production AI engineering and the skills that companies look for. I've been in the AI space for the past 3-4 years. I finished my undergrad a year ago, got into a master's at a very good university, got my first AI internship before I graduated undergrad, and now I've been at a big tech company full time on an AI team for close to a year (while doing my masters).

I know what it took for me to get my first internship. I know what I focused on and learned in my first internship to get into this competitive field early in my career, before having a master's and competing with other people that had master's and PhDs (because on my team I have a bunch of master's and PhDs and I was also told that I was the first undergrad to be in my internship). I also know. Every day, seeing what we need, what we do, and what we focus on when building our production AI systems, I know what the companies are focusing on and I know what works and what doesn't.

Again this is for AI engineering not AI research. The point I'm trying to make is that I'm trying to write a blog post that explains what you need to learn to do production AI and to build production AI systems they could attract employers. It'd be really helpful to have some advice or even to have people review the blog (just so I know that I'm providing good enough value and I'm not biased toward my own limited views).

Dm if interested

Hi, Im teen who is interested in becoming an AI Engineer, but I'm still at the stage where I honestly have no idea where to start.

I'd really appreciate answers from people who are currently working as AI Engineers / ML Engineers / in closely related roles, especially people with a few years of experience.

I'd love to know:

• What skills do you actually use in your day-to-day job?
• What should someone learn first if they're starting from basically zero?
• Which skills are genuinely important for getting hired, and which ones are overrated?
• What does a realistic AI Engineer career path look like?
• What was your own path into the field?
• What programming languages, frameworks, cloud tools, etc. should I focus on?
• How important are degrees, certifications and personal projects?
• What is the typical salary range in your country/region?
• How much can experienced AI Engineers realistically earn?
• What is your work-life balance actually like?
• Do you work remotely? If so, how flexible is it really?
• Can this career realistically allow you to travel and work from different places, or are there still a lot of restrictions?
• If you could start again, what would you learn earlier or do differently?

One of my bigger goals is to have a good income without being completely tied to a 9 - 5 lifestyle. I love travelling and would eventually like the freedom to explore different countries while still having a strong career/income.

So I'm also curious about the different paths beyond a normal full-time job like freelancing, consulting, remote work, building AI products / businesses, etc.

If you're already working in AI, I'd really appreciate hearing what your actual life looks like rather than just the job description.

Thanks! :)

Hey guys i am working as a developer and I see lot of things about harness engineering, so basically harness engineering is the approach where we can build reliance system in AI agent instead of LLM does everything

I research about harness engineering

So my mind can we build harness agent, or like specialized ai agent for specific field knowledge instead of everything knows

Anyone here interested to know about that

I’m a recent engineering graduate and I’ve recently started/will soon be starting my first full-time job in a field that is quite different from what I eventually want to do.

My long-term interest is in AI/ML. I’ve spent some time learning and working on ML-related projects during college, and I genuinely enjoy it. I would eventually like to work as an ML/AI engineer.

However, my current job is in a more traditional engineering domain, and I’m unsure whether I should:

* Continue in my current field and learn AI/ML alongside my job
* Try to move internally into an AI/data-related role
* Build my skills for 1–2 years and then switch directly into AI/ML
* Consider doing a Master's in AI/ML later

My biggest concern is that if I spend the next few years working in a completely different domain, I’ll become too far removed from AI/ML and employers won't consider me for entry-level AI roles anymore.

At the same time, I don't want to throw away a good job without having a realistic alternative.

For people who have made a career transition from one engineering field into AI/ML:

What would you do in my situation? What would you focus on during the next 2–3 years to make the transition realistically possible?

I’d especially appreciate honest advice from people who have actually made a similar transition, rather than generic career advice.

So I am doing btech in CS AI-ML . And currently I am in 3rd sem . So this semester in my syllabus the subjects are : COA ( Computer organisation & Architecture)

data structures

AI

Python

And maths for ai-ml

So the thing is after doing everything I got sometime like while traveling, before sleeping. And I want to invest that time on something productive . So I want to study some books related to Ai-ml . I really want to be good in this field so please suggest a book with which I should start with . I'll try to read 5-10 pages daily . Pls suggest something directly related to ai-ml ( not python or maths ) . And if you give me an order wise list of multiple books then that would be much more great.

Thanks you !

Basically I try to learn ML to get a role in the AI Related not exactly a ML engineer. So for that learning from the basics like Math concepts and back propagation etc., every topic that used to train our model from scratch is a better method of learning or

2: RAG, LLM related topics , MCP, Agentic AI learn how they actually work instead of going deep into the actual structure(basically exclude the math and how model trained).

Which way of learning is good for future?

Why do I ask this means every job application I go through I only see the latest topic not the core of ML. In my opinion, Learning the upper layer of AI is pretty simple when compared to going deep into math like back propagation,math concepts,and gradient descent etc,. Is spending time on learning everything is worth the time?

​

I’m currently pursuing a B.Com degree in India and also working in a BPO. I’m interested in technology, startups, marketing, and AI, and I want to seriously transition into the tech/AI field rather than staying in my current career.

I have some basic programming knowledge from Java/BlueJ, but I’m not professionally trained in computer science.

My current plan is:

Web Development → Python → Machine Learning → Deep Learning → Transformers/LLMs → AI Engineering

I’m willing to spend around 2–4 hours every day for the next 1–2 years learning and building projects.

My main concerns are:

How difficult will it be to get a software/AI job with a B.Com instead of B.Tech/CS?

Can a strong portfolio and real projects realistically compensate for the degree disadvantage?

Which roles should I realistically target — Web Developer, Python Developer, AI Engineer, ML Engineer, or AI Application/LLM Engineer?

Is my learning sequence practical, or should I change it?

What skills should I prioritize to become employable as quickly as possible?

Should I focus on getting a web/software job first and then move into AI, or directly target AI after learning the fundamentals?

For someone starting from this position, what would a realistic 2-year roadmap look like?

I’m not looking for motivation. I’d appreciate honest advice from people who have actually hired, worked in, or transitioned into software/AI without a traditional CS degree.

If you were in my position, what would you do?

Hi, I recently graduated from a tier-3 city and am currently struggling to master the foundational principles of AI/ML. I want to build solid theoretical knowledge and gain practical, hands-on experience.

Could you share some insights and project ideas that are highly relevant to the AI landscape of 2026–2027?

I am particularly interested in projects involving ML pipelines, RAG pipelines, Agentic AI, and AI agent workflows.

I've fundamental knowledge of the ML algorithms, RAG, LLM, Agentic AI. But I can't build the entire workflow/system/project by own. I always been relie on AI.

So, gives me the GitHub repos, Ideas, Tips/Tricks to remember the building cycle, cloud technology for deployment.

I'm expecting that you can provide me better response and resources and making myself and other's industry ready AI Engineer for the upcoming years.

🔴DO NOT suggest like AI roadmaps, AI generated answers, already passed info's

#AIexperts #MLexperts #AIMLrecruiters #AI2026