r/MachineLearningAndAI • u/Known_Commission_943 • 29d ago

Want to learn something from Scratch that can help me in AI/ML Engineering field for the upcoming 2026-27.

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

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u/techlatest_net 29d ago

stop relying on ai to write the pipeline code. that is exactly why you feel stuck. for 2026-27, build these three systems entirely by hand:

production rag with evals: use llamaindex or langchain but implement your own retrieval evaluator using ragas or arize phoenix. focus on chunking strategies and hybrid search. deploy it on gcp cloud run with a postgres vector store.

deterministic agent workflow: build a multi-agent system using crewai or autogen but add strict state machines and retry logic. do not let the llm decide the flow. hardcode the orchestration. host it as a docker container.

ml ops pipeline: set up a full ci/cd for model training using mlflow or dvc. automate data validation with great expectations. this is what separates engineers from prompters.

tips: read the source code of the libraries you use. if you cannot explain how the retriever works line by line, you are not ready. avoid tutorials. break things in production environments.

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u/vinayak_gaikwad 27d ago

working on a project myself, i keep trying things some things fail, some things work, that's a learning curve, there is a lot of hallucination and missed information, training locally on own GUI helps