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I am a Senior Machine Learning Engineer with 8+ years of experience in NLP, computer vision, and deep learning, specializing in Agentic AI, RAG, and LLM fine-tuning (LoRA/QLoRA, RLHF). I design and deploy scalable AI systems across healthcare and financial domains, with a strong focus on HIPAA/GDPR compliance and ethical AI. I excel at cross-functional leadership, mentoring, and delivering business impact. From healthcare voice assistants to document AI and internal code agents, I build end-to-end solutions that improve efficiency and user experience, while driving innovation and responsible deployment.…I am a Senior Machine Learning Engineer with 8+ years of experience in NLP, computer vision, and deep learning, specializing in Agentic AI, RAG, and LLM fine-tuning (LoRA/QLoRA, RLHF). I design and deploy scalable AI systems across healthcare and financial domains, with a strong focus on HIPAA/GDPR compliance and ethical AI. I excel at cross-functional leadership, mentoring, and delivering business impact. From healthcare voice assistants to document AI and internal code agents, I build end-to-end solutions that improve efficiency and user experience, while driving innovation and responsible deployment.

Tadej Bukovec

Data Scientist, AI Engineer, AI Developer, +5

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I am a Senior Machine Learning Engineer with 8+ years of experience in NLP, computer vision, and deep learning, specializing in Agentic AI, RAG, and LLM fine-tuning (LoRA/QLoRA, RLHF). I design and deploy scalable AI systems across healthcare and financial domains, with a strong focus on HIPAA/GDPR compliance and ethical AI. I excel at cross-functional leadership, mentoring, and delivering business impact. From healthcare voice assistants to document AI and internal code agents, I build end-to-end solutions that improve efficiency and user experience, while driving innovation and responsible deployment.…I am a Senior Machine Learning Engineer with 8+ years of experience in NLP, computer vision, and deep learning, specializing in Agentic AI, RAG, and LLM fine-tuning (LoRA/QLoRA, RLHF). I design and deploy scalable AI systems across healthcare and financial domains, with a strong focus on HIPAA/GDPR compliance and ethical AI. I excel at cross-functional leadership, mentoring, and delivering business impact. From healthcare voice assistants to document AI and internal code agents, I build end-to-end solutions that improve efficiency and user experience, while driving innovation and responsible deployment.

Available to hire

I am a Senior Machine Learning Engineer with 8+ years of experience in NLP, computer vision, and deep learning, specializing in Agentic AI, RAG, and LLM fine-tuning (LoRA/QLoRA, RLHF). I design and deploy scalable AI systems across healthcare and financial domains, with a strong focus on HIPAA/GDPR compliance and ethical AI.

I excel at cross-functional leadership, mentoring, and delivering business impact. From healthcare voice assistants to document AI and internal code agents, I build end-to-end solutions that improve efficiency and user experience, while driving innovation and responsible deployment.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Java

Intermediate

C++

Intermediate

Language

English

Fluent

Work Experience

Senior Machine Learning Engineer at Eleks

August 1, 2023 - Present

Led the development and deployment of a travel booking system powered by Agentic AI (ASR, LLM, and AI avatar) using LangChain, LangGraph, Livekit, and Heygen, integrating OpenAI and Claude APIs to enable targeted campaigns, increasing booking rates by 22%. Built a scalable hybrid knowledge base (vectorDB + relational DB) with pgvector and FAISS; improved retriever performance via semantic chunking and document-based chunking. Optimized model serving using vLLM and TensorRT-LLM on AWS/GCP, increasing GPU utilization by over 30% and reducing time-to-first-token by 0.8s. Designed conversational agents to extract metadata from raw databases in PowerBI and Databricks via Text-to-SQL, improving data quality. Fine-tuned 7+ open-source LLMs (including instruction tuning) and applied reinforcement learning from human feedback (PPO/DPO/GRPO) for internal code agents. Delivered 5+ Generative AI solutions including code agents (Claude Code, Cursor) with MCP-based code/data management.

Remote AI Engineer at Notable Health

August 1, 2023 - October 16, 2025

Fine-tuned over 10 LLMs for healthcare document summarization and conversational AI using PEFT (QLoRA and related techniques), reducing memory usage by 70% and speeding up training by ~2x. Built a healthcare voice assistant leveraging knowledge base and prompting strategies (query expansion, chain-of-thought) with LangChain, LangGraph, CrewAI, Haystack, and LlamaIndex. Constructed the knowledge base using vector DBs (Weaviate, pgvector) and Graph DB (Neo4j), and built a Hybrid RAG combining keyword and semantic search (SBERT) with re-ranking (CoIBERT) to reduce hallucinations. Applied RLHF with 500+ professionals, with source citations and guardrails to ensure HIPAA/GDPR/PHI compliance. Deployed real-time data prediction to transform raw mobile sensor data into a Data Lake using anomaly detection (DBSCAN, k-means) across 100M transactions monthly.

Remote Machine Learning Engineer at Meta

June 1, 2020 - October 16, 2025

Developed a customer activity prediction system with XGBoost using scikit-learn and MLflow, achieving 92% classification accuracy. Built a sentiment analysis pipeline processing 10,000 daily reviews with TensorFlow, spaCy, and NLTK, achieving high accuracy, and implemented text summarization using BART with ROUGE-1 score of 40 for 60,000 product descriptions. Leveraged Tableau for exploratory data analysis to accelerate model development and hypothesis validation. Built robust ETL pipelines with PCA, t-SNE, and UMAP using Pandas, PySpark, Kafka, and Airflow. Developed automatic license/number plate recognition using OpenCV and YOLOv5, optimized for mobile with ONNX, Keras, and PyTorch, automating pipelines and saving thousands of hours.

Senior Machine Learning Engineer at Eleks

August 1, 2023 - Present

Led the development and deployment of a travel booking system powered by Agentic AI (ASR, LLM, and AI avatar) using LangChain, LangGraph, Livekit, Heygen, and various APIs (OpenAI, Claude). Achieved a 22% increase in booking rates through targeted campaigns. Designed scalable hybrid knowledge base (vectorDB + relational DB) with pgvector and FAISS; improved retriever with semantic chunking. Optimized model serving with vLLM and TensorRT-LLM on AWS/GCP, increasing GPU utilization by 30% and reducing time-to-first-token by 0.8s. Created conversational agents to extract metadata from raw databases on PowerBI and Databricks; implemented Text-to-SQL and Data Quality improvements. Fine-tuned 7+ open-source LLMs with RLHF; selected internal code agents. Delivered 5+ Generative AI solutions including code agents; implemented MCP protocol for data/code management and built an intelligent internal assistant.

Remote AI Engineer at Notable Health

August 1, 2023 - October 16, 2025

Fine-tuned 10+ LLMs for healthcare document summarization and conversational AI using PEFT (QLoRA, Deepspeed); memory usage reduced by 70%, training speed doubled. Built a healthcare voice assistant with knowledge base using prompt engineering, LangChain, LangGraph, CrewAI, Haystack, LlamaIndex. Constructed a knowledge base using vectorDBs (Weaviate, pgvector) and a Graph DB (Neo4j); implemented Hybrid RAG with SBERT reranking to reduce hallucinations. Employed RLHF with 500+ professionals and source citations to improve factuality; implemented guardrails to satisfy HIPAA/GDPR/PHI compliance. Deployed real-time data prediction to transform raw mobile sensor data into Data Lake using anomaly detection (DBSCAN, K-means), improving recall and reducing false positives across large-scale data flows.

Machine Learning Engineer at Meta

June 1, 2020 - October 16, 2025

Developed a customer activity prediction system with XGBoost and MLflow; achieved 92% classification accuracy. Built a sentiment analysis pipeline (TensorFlow, SpaCy, NLTK) with 97% accuracy; implemented text summarization using BART with ROUGE-1 of 40 for 60k product descriptions. Performed EDA in Tableau; built ETL pipelines with PCA, t-SNE, UMAP; used Kafka and Airflow for data workflows. Implemented automatic license/number plate recognition using OpenCV and YOLO5; optimized for mobile using ONNX, Keras, PyTorch.