For employers

Hire this AI Trainer

Sign in or create an account to invite AI Trainers to your job.

LoginCreate account
Invite to Job
D

Daniel Florea

LLM Fine-Tuning and AI Training Specialist (Senior AI Engineer, Cognigy)

Romania flagRemote, Romania
$40.00/hrExpert

Key Skills

Software

No software listed

Top Subject Matter

Conversational AI
Automotive Retail
Developer Marketplaces

Top Data Types

TextText
Computer Code ProgrammingComputer Code Programming
DocumentDocument

Top Task Types

Fine-tuningFine-tuning
Text GenerationText Generation
Computer Programming/CodingComputer Programming/Coding
Data CollectionData Collection
TranscriptionTranscription

Freelancer Overview

LLM Fine-Tuning and AI Training Specialist (Senior AI Engineer, Cognigy). Brings 11+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Internal and Proprietary Tooling. Education includes Bachelor's Degree, Technical University of Cluj-Napoca (2016). AI-training focus includes data types such as Text and labeling workflows including Fine-tuning.

ExpertEnglish

Labeling Experience

LLM Fine-Tuning and AI Training Specialist (Senior AI Engineer, Cognigy)

TextFine Tuning
Fine-tuned large language models (LLMs) such as OpenAI GPT, Anthropic Claude, Mistral, Llama, and Gemini for domain-specific tasks using LoRA and QLoRA techniques. Orchestrated hybrid intent architectures that combined fine-tuned classifiers and LLM reasoning layers for conversational system robustness. Designed RAG pipelines and integrated retrieval architectures to mitigate hallucinations and ensure reliable data grounding.• Led prompt engineering and instruction optimization for LLM-based conversational agents • Established validation and review processes for LLM outputs to ensure quality and compliance • Created, curated, and annotated large textual datasets for supervised model training and evaluation • Defined and enforced high-integrity data labeling standards for multi-agent AI systems

Fine-tuned large language models (LLMs) such as OpenAI GPT, Anthropic Claude, Mistral, Llama, and Gemini for domain-specific tasks using LoRA and QLoRA techniques. Orchestrated hybrid intent architectures that combined fine-tuned classifiers and LLM reasoning layers for conversational system robustness. Designed RAG pipelines and integrated retrieval architectures to mitigate hallucinations and ensure reliable data grounding.• Led prompt engineering and instruction optimization for LLM-based conversational agents • Established validation and review processes for LLM outputs to ensure quality and compliance • Created, curated, and annotated large textual datasets for supervised model training and evaluation • Defined and enforced high-integrity data labeling standards for multi-agent AI systems

2023 - Present

LLM Fine-tuning & AI Training (Senior AI Engineer, Apptension)

TextFine Tuning
Applied LoRA and SFT fine-tuning to transformer-based NLP models, training both generative and classification solutions for high-traffic hotel price comparison platforms. Designed hybrid intent routing pipelines with labeled data to enable context-aware LLM scoring. Built domain-specific RAG systems and ensured data-backed, hallucination-resistant AI responses.• Developed and labeled intent and classification datasets for LLM and transformer models • Conducted manual review and labeling of domain-specific text data for supervised fine-tuning • Validated output accuracy and correctness for pricing and availability conversational AI workflows • Implemented best practices in LLM data preparation and annotation for large-scale deployments

Applied LoRA and SFT fine-tuning to transformer-based NLP models, training both generative and classification solutions for high-traffic hotel price comparison platforms. Designed hybrid intent routing pipelines with labeled data to enable context-aware LLM scoring. Built domain-specific RAG systems and ensured data-backed, hallucination-resistant AI responses.• Developed and labeled intent and classification datasets for LLM and transformer models • Conducted manual review and labeling of domain-specific text data for supervised fine-tuning • Validated output accuracy and correctness for pricing and availability conversational AI workflows • Implemented best practices in LLM data preparation and annotation for large-scale deployments

2018 - 2023

Education

T

Technical University of Cluj-Napoca

Bachelor's Degree, Information Technology

Bachelor's Degree
2012 - 2016

Work History

C

Cognigy

Senior AI Engineer

Remote
2023 - Present
A

Apptension

Senior AI Engineer

Remote
2018 - 2023