Hello, I'm Amir 👋

AI/ML Engineer building production LLM & RAG systems

Projects

Selected Projects

Architecture diagram: documents, Celery ingestion, Qdrant and OpenSearch, hybrid search, cited LLM answers, FastAPI and PostgreSQL, observability

Multi-Tenant RAG Platform

2026 – Now

Secure document search and AI chat across workspaces, with RBAC, JWT auth and tenant isolation. Async ingestion (OCR, chunking, embedding), hybrid retrieval (Qdrant + BM25 with RRF and reranking), cited answers, and Prometheus/OpenTelemetry observability with Recall@K, MRR and nDCG evaluation.

Architecture diagram: Next.js dashboard, FastAPI, provider router, ComfyUI and cloud providers, image, video and upscaling pipeline

AI Fitness Video Studio

2026 – Now

Full-stack AI video generation platform for consistent fitness videos from reusable characters, environments and prompt templates. Provider-agnostic layer over local ComfyUI and cloud models, async job orchestration, and a Next.js dashboard for assets, prompts and job tracking.

Architecture diagram: resumes, Hugging Face embeddings, pgvector, ranked candidates, job description enhanced by OpenAI via Django API

Resume Matching System

2025

Ranks candidates against job descriptions with semantic embeddings and pgvector search. Hugging Face embeddings, OpenAI-powered job description enhancement, and background processing with Celery, Redis and Docker.

Architecture diagram: PDF extraction, MongoDB, LLM, validation and repair, bilingual questions via Flask API, interactive HTML quiz

Question Generating App

2025

Freelance AI service that turns PDFs into bilingual (Persian/English) multiple-choice questions. Semantic chunking, duplicate detection, answer validation, retry and response repair, with unit-tested core components.

From research to production. I build LLM applications, retrieval pipelines and backend systems that are measurable, observable and ready to scale. Models are only useful once they ship.

Portrait of Amir Esmaeili
About

I am a Backend Developer Turned AI/ML Engineer

I specialize in production LLM applications, Retrieval-Augmented Generation and scalable backend systems, from AI services and vector search to distributed ML infrastructure. I'm completing an M.Sc. in Soft Computing and Artificial Intelligence at the University of Tabriz on a full scholarship. Based in Tabriz, Iran, and open to relocation.

Years of experience5+
Service points optimized100+
Fewer service delays30%
Less manual oversight40%
Career

And This Is My Career

AI/ML Engineer at NetPardazAzar 09/2026 - Now

Building AI and machine learning solutions, applying my LLM, RAG and backend experience to production systems.

AI/ML Engineer at Desmer Guvenlik 02/2024 - 03/2026

Deployed AI optimization models for logistics across 100+ service points, cutting service delays by 30%. Used causal inference to evaluate process changes (20% fewer delivery delays), integrated ML into live systems (40% less manual oversight), and forecast ATM cash demand across 50+ locations, reducing cash shortages by 25%.

Backend Developer at Aral Studio 02/2023 - 01/2024

Designed real-time backend systems for high user traffic with excellent uptime. Improved API response time by 35% through refactoring and database indexing across 10+ endpoints, and architected microservices that cut deployment time by 40%.

Backend Developer at NOAY 09/2021 - 01/2023

Built secure, scalable backend infrastructure for a cryptocurrency platform handling high-frequency transactions with near-zero failures. Developed APIs and microservices that reduced server load by 25%, working closely with frontend teams.

Education

Academic Background

M.Sc. Soft Computing & AI, University of Tabriz 2023 - Now

Selected as a "Brilliant Talent" with direct admission and a full scholarship. Grades: Artificial Intelligence A, Data Mining A+, Deep Learning B+, Machine Learning B.

B.Sc. Computer Science, University of Tabriz 2019 - 2023

Full scholarship, ranked 4th in overall GPA, top 3% in the national university entrance exam, and honorable mention at the ICPC in 2019, 2020 and 2021.

Why me?

I'll help your AI project ship

End-to-End Pipelines

From ingestion, chunking and embeddings to hybrid retrieval, reranking and cited answers, I own the whole RAG stack.

Measurable Impact

Delivered 30% fewer service delays and 25% fewer cash shortages. I evaluate with Recall@K, MRR and nDCG, not vibes.

Production-Ready

Auth, tenant isolation, async workers, Docker and observability with Prometheus, OpenTelemetry and Grafana.

Podcast

Off the Clock, On the Mic

Away from engineering, I host a podcast called 91.8 Radio. New episodes are shared only on my Telegram channel.

Only on Telegram

91.8 Radio

Relaxed conversations away from the keyboard. 2 episodes so far, with more on the way.

18:2442:10
Contact

Let's Get in Touch

Have an LLM, RAG or backend project in mind? Let's talk.

Send an email Or find me on LinkedIn