u/abhiramputta

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Need Help with Placements? I’m Offering Free AI/ML Career Guidance

I remember how confusing it was when I was preparing for placements.

Questions like:

\- Is my resume good enough?

\- What projects should I build?

\- Should I focus on DSA, ML, or GenAI?

\- How do I get shortlisted?

A lot of people don't need another paid course—they just need someone to point them in the right direction.

So here's what I'd like to do.

For the next few weeks, I'm offering FREE:

\- Resume reviews

\- Career guidance for AI, ML, and GenAI

\- Project suggestions based on your current skill level

\- Interview preparation advice

\- Learning roadmap recommendations

A little about me:

\- AI Engineer working on production GenAI systems

\- Previous Data Science Intern at Siemens Healthineers

\- Experience building enterprise RAG pipelines and AI applications

I'm not selling anything through these sessions. If I can help you avoid some of the mistakes I made, that's enough.

If you're a student, a recent graduate, or someone trying to transition into AI/ML, feel free to book a session here:

https://topmate.io/abhiram_putta/

If I receive a lot of requests, I'll review them on a first-come, first-served basis.

Let's help each other grow. 🚀

​

Need Help with Placements? I’m Offering Free AI/ML Career Guidance

I remember how confusing it was when I was preparing for placements.

Questions like:

- Is my resume good enough?

- What projects should I build?

- Should I focus on DSA, ML, or GenAI?

- How do I get shortlisted?

A lot of people don't need another paid course—they just need someone to point them in the right direction.

So here's what I'd like to do.

For the next few weeks, I'm offering FREE:

- Resume reviews

- Career guidance for AI, ML, and GenAI

- Project suggestions based on your current skill level

- Interview preparation advice

- Learning roadmap recommendations

A little about me:

- AI Engineer working on production GenAI systems

- Previous Data Science Intern at Siemens Healthineers

- Experience building enterprise RAG pipelines and AI applications

I'm not selling anything through these sessions. If I can help you avoid some of the mistakes I made, that's enough.

If you're a student, a recent graduate, or someone trying to transition into AI/ML, feel free to book a session here:

"https://topmate.io/abhiram\_putta/" (https://topmate.io/abhiram\_putta/)

If I receive a lot of requests, I'll review them on a first-come, first-served basis.

Let's help each other grow. 🚀

I'm an AI Engineer with about 1 year of industry experience and currently earn 20+ LPA.

Most of my work so far has been around building and maintaining RAG-based applications. I've worked on:

- Document ingestion and preprocessing pipelines

- Chunking, embeddings, and retrieval optimization

- Vector databases and semantic search

- Prompt engineering

- LLM integration and evaluation

- Knowledge-grounded chatbots and enterprise search systems

- API development and deployment of AI applications

- End-to-end RAG workflows from data ingestion to production deployment

The compensation and learning have been good, but I feel my exposure has largely been limited to implementing and productizing existing AI solutions rather than working on the research side of AI.

Areas where I have little or no exposure:

- AI research

- Fine-tuning large models

- Training models from scratch

- LLM architecture and internals

- Advanced agentic systems

- Multimodal AI

- Research publications and paper implementation

Long term, I want to grow toward the research side of AI rather than staying purely in application development.

Questions for experienced AI Engineers, Research Engineers, and Applied Scientists:

1. How do I avoid getting pigeonholed as a "RAG Engineer"?

2. What skills should I focus on over the next 2–3 years?

3. Is it worth moving toward research, or should I double down on AI Engineering and Agentic AI?

4. What kinds of projects help in landing freelance AI work?

5. How can I gain research-oriented experience when my current organization doesn't offer opportunities in that area?

I'm also looking for research topics that are practical enough for an industry engineer to start exploring independently. Some areas I'm considering are:

- Agentic AI and multi-agent systems

- RAG evaluation and retrieval optimization

- Long-context reasoning in LLMs

- Small Language Models (SLMs) and efficient fine-tuning

- Multimodal AI (text, image, document understanding)

- LLM benchmarking and evaluation frameworks

- AI for healthcare applications

- Synthetic data generation

- Knowledge graphs + LLMs

- Hallucination detection and mitigation

For those already working in research or applied research, which of these areas has the highest potential over the next few years, and what would be a realistic roadmap for someone coming from a primarily RAG-focused background?

Would appreciate advice from people who have made a similar transition.

How are people getting freelance work in AI right now?

I’m an AI Engineer with ~1.5 years of experience and recently I’ve been spending time building with RAG systems, multi-agent workflows, retrieval optimization, and LLM applications.

One thing I’m trying to understand is how people actually find freelance opportunities in this space.

Are most projects coming from:

- Upwork / freelancing platforms?

- Open-source contributions?

- LinkedIn / X networking?

- Startup communities?

- Building in public?

- Referrals?

I’m less interested in generic web dev work and more curious about AI engineering projects (agents, RAG, automation, internal copilots, etc.).

Would love to hear how people got their first few projects and what worked for them.

Hi everyone, I’m planning to purchase a flat in Vrindhavan by Namishree. I really liked the project, but I’m still unsure about the builder and the overall reliability of the project.

Would love to hear your thoughts or experiences with Namishree. Also, please let me know if there are any issues or red flags I should be aware of before making a decision.