ML & Applied AI Engineer

Milan MilenkovicML & Applied AI Engineering

I ship production LLM features, agentic workflows, and RAG systems in React and Node — for products that need AI that works at scale, not just demos.

No spam. No obligations.

Milan Milenkovic — ML & Applied AI Engineer

Milan Milenkovic

I'm an ML & Applied AI Engineer and full-stack developer. I build production ML pipelines, integrate LLMs, develop agentic systems, and ship RAG pipelines into live products — alongside the search, auth, and infrastructure they run on. Available for contract work with EU and US clients.

What I do

ML & Applied AI engineering, end to end

LLM integration, agentic systems, and RAG in React/Node. Full-stack is how I deliver — not a separate service line.

LLM features in production

RAG, structured output, streaming, and prompt orchestration — integrated into your React/Node product and built to survive real traffic.

Agentic systems

AI agents with tool use, function calling, and autonomous workflows that take real actions inside your product — not just generate text.

Full-stack delivery

React, Next.js, Node.js, vector DBs, deployment — I own the stack end to end so your AI features actually ship, not stall in a notebook.

ML & Applied AI Engineering

How I build with AI

From retrieval and structured LLM output to agents that call tools and automate workflows — engineered for production in the JavaScript stack.

RAG systems

Ground LLMs in your data with embeddings, vector search, and retrieval tuned for your domain.

LLM app development

Structured output, streaming, prompt orchestration, and safe integrations that survive production traffic.

Agentic code & automation

Agents with tool use, function calling, and multi-step reasoning that automate real workflows inside your codebase and product.

Evals & observability

Testing, evaluation, and monitoring so AI features stay accurate after launch.

OpenAILangChainVector DBspgvectorAgentsReactNode.js
Work

Shipped & live

Real products with real users — numbers included, not just adjectives.

najdiavto.com

LiveAI search live
200+car brands
212municipalities
AINL search

Production car marketplace with real dealer inventory — faceted search plus natural-language AI search across fuel, transmission, body type, color, doors, and Euro norm.

ReactViteNode.jsMongoDBVercelRAG
View case study

kembo.app

LiveFree tier · Pro plans
4platform SDKs
OAuthhosted flow
Prodmode ready

Hosted auth infrastructure for mobile and web — OAuth, short-lived JWTs with rotating refresh tokens, hashed sessions, role-based user management.

ExpoFlutterCapacitorWeb SDKNode.js
Visit site

signpad.online

Live
0installs needed
100%in-browser
Freeto use

Browser PDF workspace — upload, edit, annotate, and sign documents with no install, no ads, and a proper landing page.

ReactNext.jsPDF.jsNode.js
Visit site
Labs

ML Projects & experiments

Open-source ML projects that demonstrate specific techniques — from NLP to recommendation systems.

najdiavto-ml

LiveCase study
0.86MRR (LTR)
62eval queries
4MLOps phases

End-to-end ML service for a car marketplace — price intelligence, hybrid search, learning to rank, and MLOps with monitoring and safe retraining.

Pythonscikit-learnLightGBMFastAPIMLflowDocker
View case study

comment-sense

LiveCase studyFeedback loop
3languages
6categories
HybridML + lexicon

Multilingual NLP demo — sentiment analysis and text classification in English, Serbian, and German with a feedback loop for continuous improvement.

Pythonscikit-learnHuggingFaceFastAPIReactDocker
View case study

matchmaker

LiveCase study
9,700+movies
HybridSVD + content
3languages

Hybrid movie recommendation engine — collaborative filtering (SVD) + content-based genre similarity. Powered by MovieLens dataset with 9,700+ films.

Pythonscikit-learnscikit-surpriseFastAPIReactDocker
View case study

automl-lite

LiveCase study
3models
Autofeature detection
best model

Automated ML pipeline — upload data, train regression models (LinearRegression, Ridge, RandomForest), compare metrics, and make predictions. No code needed.

Pythonscikit-learnFastAPIReactDocker
View case study
How I work

Direct, fast, production-minded

You work with me — not a sales team, not a rotating cast of juniors. I scope honestly, ship weekly, and care about what happens after launch.

What you get

  • Short feedback loops — you see working software every week
  • Direct communication, no account-manager layer
  • Production-first: metrics, latency, and reliability matter
  • Clean, maintainable code you can hand off
  • Available for focused contracts, not endless scope creep

Have a project in mind?

Tell me what you're building — I'll get back within 24 hours. No obligations, fully confidential.