Hey everyone,

I'm currently a Security Engineer at Deloitte, but my heart (and most of my GitHub activity) is still firmly in ML Systems and Backend.

I recently moved from a fast-paced startup environment (Cinntra) to Deloitte because I wanted to see how the "enterprise" world scales things and learn the professional rigour of a massive firm. While I've learned a lot about IAM and SailPoint here, I've realized I'm way more effective when I'm actually building Al pipelines and optimizing inference rather than just securing them.

The TL;DR on my background:

Past Work: Spent ~1 year as an ML Systems

Engineer at a startup. Built enterprise RAG pipelines and fine-tuned LLaMA models, bumping task accuracy by ~20% and cutting iteration time by 35% through better CI/CD.

Currently: Working as a Security Engineer by day,

but still acting as an independent Al Systems Engineer by night. Just finished a Dockerized RAG pipeline with 92% retrieval relevance and p50 latency of 320ms.

Tech Stack: Python, TypeScript, Rust, PyTorch, LangChain, Docker/K8s, and the usual suspects (PostgreSQL, Redis, AWS).

What I've actually done:

Fine-tuned LoRA adapters + 8-bit quantization to cut inference costs by ~38%.

Built a cross-platform Agentic AI (R.I.M.A.S) using YOLOv8 and LLAMA.

Designed zero-knowledge encryption platforms for fun (HashKrypt).

Things aren't really clicking at the big "D" right now, and I'm looking to jump back into an ML Systems, Al, or Backend role where I can actually ship code.

If your team is hiring or you can hook me up with a referral, I'd really appreciate it. Happy to chat in the DMs!


ML Systems Engineer / Backend Dev looking for a pivot back to Al (1.2+ YOE)