Walk in for non Tech roles : 26th-28th.
Role : Non Technical Role:
Location : Hyd
Education Qualification : Any Graduate/Pos Grad.
Skills : Exceptional Communication skills are mandatory
If anyone interested please DM me I will give the details.
Note: Please if are not graduate or if you don't have good communication skills don't DM me and don't waste my time..
#FresherJobs
We’re building the next generation of enterprise AI agents and are urgently hiring hands-on AI/ML Data Engineers who live and breathe Large Language Models and Retrieval-Augmented Generation (RAG) systems.
What you’ll do day-to-day
- Design, build, and productionize RAG pipelines (ingestion → chunking → embedding → indexing → retrieval → generation)
- Fine-tune and align open-source LLMs (Llama 3, Mistral, Mixtral, Phi-3, Gemma, etc.) as well as work with closed models via API
- Own the full data lifecycle for training/fine-tuning: data cleaning, synthetic data generation, evaluation datasets, human feedback loops (RLHF/DPO)
- Build scalable feature stores, vector databases, and knowledge graphs on Azure
- Implement evaluation frameworks (RAGAS, DeepEval, custom LLM-as-Judge, etc.) and continuously improve answer quality & latency
- Collaborate with ML researchers and full-stack engineers to ship AI features used by millions
Must-have skills & skills
- 4+ years of professional data/ML engineering experience
- Deep, hands-on experience shipping production RAG systems and/or fine-tuning LLMs
- Very strong Python (we write production code, not just notebooks)
- Expert-level knowledge of Azure cloud (Azure ML, Azure AI Search, Azure Cosmos DB / PG Vector, Azure OpenAI Service, AKS, Blob Storage, Data Factory, etc.)
- Proficiency with modern ML stack: LangChain/LlamaIndex/Haystack, Pinecone/Weaviate/Qdrant/Milvus (or Azure equivalents), PyTorch/TensorFlow/JAX, Hugging Face ecosystem, vLLM/TGI/OpenAI-compatible servers
- Experience with prompt engineering, chain-of-thought, agents, tool calling, and advanced RAG techniques (HyDE, parent-document, metadata filtering, reranking, etc.)
- Solid software engineering practices (CI/CD, testing, observability, cost optimization)
Big pluses
- Previously published or contributed to open-source LLM/RAG projects
- Experience with RLHF pipelines (TRL, TRLX, Argilla, LabelStudio)
- Knowledge of quantization, distillation, LoRA/QLoRA, or inference optimization
- Previously worked at high-growth AI startups or FAANG-level AI teams
Compensation & benefits
- Highly competitive salary ($180k–$280k+ base depending on seniority & location)
- Generous equity (0.5%–2%+)
- Fully remote (strong preference for candidates with ≥4h overlap with US East or West Coast)
- Unlimited PTO, top-tier health insurance, 401(k) match, learning budget, latest hardware
Introducing Gemini 3 ✨
It’s the best model in the world for multimodal understanding, and our most powerful agentic + vibe coding model yet. Gemini 3 can bring any idea to life, quickly grasping context and intent so you can get what you need with less prompting.
Find Gemini 3 Pro rolling out today in the @Geminiapp and AI Mode in Search. For developers, build with it now in @GoogleAIStudio and Vertex AI.
Excited for you to try it!
I truly had an amazing time interacting with the students at @IITHyderabad
When I asked, “How many of you want to get married?” — more men raised their hands, than the women!
The women seemed far more career-focused !!!!
This is the new - Progressive India. 🇮🇳
Set your vision.
Define your goals.
Own your role.
And watch yourself become unstoppable.
EDUCATION is DEAD
Hey students wake up and CELEBRATE the DEATH of EDUCATION
The explosion of A I will be in direct proportion to a public acknowledgement by all concerned, that our present day education system is dead
Here’s looking at the medical course for an example
A medical student spends 5 years learning about the body, 2 years doing post-graduation, and another 2 or 3 years in specialization. That’s a decade of memorizing muscles, nerves, organs, their functions and protocols , all to finally diagnose what went wrong in someone’s body to give an appropriate treatment
Now, if an AI can read millions of medical cases, scan patient data, and give a diagnosis faster, more accurately, and without bias and also suggest treatment then what’s the point of wasting 10 years on what a machine can do in 10 seconds?
A leading doctor told me something chilling
“It makes me sad to think of all those present day poor students joining medical colleges, because by the time they finish, there will be nothing left for them to do.”
That’s not dystopia. That’s the truth of today right now
And not for just medicine but for any other course
In an AI world, sticking to our present education system is not traditional .. it’s both naive and regressive.
Ours is a memory-based education system, built for a time when information was scarce. But when you have a device that can give you any information instantly, memorizing is not knowledge , it’s downright stupidity.
Forty years ago, we learned multiplication tables by heart. Then calculators came and we stopped learning tables
The naysayers said “What if our brains forget how to calculate?”
“What if the machine breaks down one day?”
That’s like saying we should also keep a horse cart ready in case the car doesn’t start.
Every revolution first sounds like a conspiracy to those who are comfortable with the past. The same fear, insecurity, and self preserving lies are being recycled now about AI.
The AI wave will not wait for universities, ministers, or outdated boards to adapt. It will simply erase what doesn’t evolve and the first victims will be the students
I believe that radical reforms in education is not a choice , but it’s for future survival.
Otherwise, today’s students will become sacrificial lambs, brutally betrayed by their ignorant parents and even more ignorant policymakers, who are proudly preparing them for jobs that will not exist.
On an immediate basis we must allow AI tools inside classrooms and exams not as cheats, but as able assistants
Schools should stop pretending to educate. They should only test how intelligently and creatively a student can use AI.
The question papers of the future shouldn’t ask what you know , they should ask how fast, how deeply, and how innovatively you can make AI work for you.
Because the new genius will not be the one who knows everything, but will be the one who knows how to ask AI the right question.
Hey Students , You are living in the eye of an AI apocalypse.
You need to realise that the ground beneath your textbooks is melting fast.
Your degrees wont be worth the paper they are printed upon
Your professors are teaching you from the ruins of a dead system.
If you keep learning the old way, you will just graduate into extinction.
AI won’t kill you .. it will simply ignore you.
So stop studying for marks and
start learning how to use A I .
Because very soon, the ones who can’t use A I, will be used up by A I
NOTE: I am willing to answer any sensible counter to what I wrote in here
Andrej Karpathy says you should learn AI depthwise, not breadthwise.
Most education is breadthwise: watch lectures, memorize formulas, and trust you'll need it later.
Karpathy flips this by learning "depthwise, on demand."
What this means:
Pick a project, start building, and learn exactly when you hit a wall.
When he created a tutorial on transformers (the architecture behind ChatGPT), he didn't start by explaining attention mechanisms or complex architectures.
Instead, he started with the simplest possible thing: a lookup table that predicts the next word.
You build that first. Then you try to make it handle more complex patterns.
And it breaks.
Only then, when you've felt the limitation, does he introduce the next concept. Each piece solves a problem you've actually encountered.
As he puts it:
"It's a dick move to present the solution before I give you a shot to try it yourself."
When you attempt the problem first, the solution actually makes sense.
Teaching forces you to learn. "If I don't really understand something, I can't explain it."
When you try to explain and stumble, you've found the gaps in your understanding.
...
Build a project that gives you a reward.
Hit a wall. Learn just enough to solve it. Then explain it to someone else.
Don't consume content. Build the code.
That's how you actually learn.
@maninekkalapudi @lanccer7 Gemini is good for general thinking but struggles with code syntax. I use Gemini to plan the task and then have Sonnet write the code.
Campaign for Judicial Accountability & Reforms (CJAR) welcomes the recent proactive disclosures by the Supreme Court bringing much needed transparency in the functioning of the judiciary. See statement below 👇
@TeluguScribe@grok ఏందీ ఈ పంచాయతీ మాకు? అస్సలమే ఎవరు? ఆమెకు ఏం అధికారం ఉంది? మహిళా కమిషనర్ ఐతే సినిమాలో ఏముండాలో ఉండద్దో ఈమెనే డిసైడ్ చేసేస్తదా? ఆ కాడికి సెన్సారు బోర్డు దేనికి?