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High Tech Engineering Center Kft.
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Munkavégzés helye
Országos lefedettség -
Munkaidő, foglalkoztatás jellege
- Teljes munkaidő
- Általános munkarend
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Elvárt technológiák
- MACHINE LEARNING DATABASES
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Elvárások
- Nem kell nyelvtudás
- 5-10 év tapasztalat
- Egyetem
Kis türelmet...
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Állás leírása
Responsibilities
Building cutting-edge multilingual transcription systems
Delivering accurate, consistent audio and text transcription across diverse media assets
Enabling automatic language and locale detection in real-world scenarios
Working with state-of-the-art LLMs and transformer-based architectures
Architecting scalable AI solutions
Fine-tuning high-impact models
Delivering accurate, consistent audio and text transcription across diverse media assets
Enabling automatic language and locale detection in real-world scenarios
Working with state-of-the-art LLMs and transformer-based architectures
Architecting scalable AI solutions
Fine-tuning high-impact models
Requirements
5+ years of industry experience
2+ years implementing LLM or NLP systems
Bachelor's (preferred Master's Degree) in Computer Science or Electrical Engineering
Hands-on experience with fine-tuning transformer models for text-to-text and audio-to-text
Experience with multi-lingual NLP
Proven track record for building ML / AI systems architecture, RAG and multi-agent systems
Deep understanding of transformer models (Huggingface, SentenceTransformers)
Experience with efficiently fine-tuning large language models (LLMs) with LoRA, QLoRA
Knowledge of model optimization techniques (quantization, pruning, distillation)
Experience with multi-modal dataset preparation and quality improvement
Multi-lingual NLP, and cross-lingual transfer learning
Familiarity with language-specific text processing (tokenization, normalization)
Deployment of resource intensive models and scalable AI systems
Monitoring model performance in production and detecting drift
Distributed training (DDP, FSDP, mixed-precision)
2+ years implementing LLM or NLP systems
Bachelor's (preferred Master's Degree) in Computer Science or Electrical Engineering
Hands-on experience with fine-tuning transformer models for text-to-text and audio-to-text
Experience with multi-lingual NLP
Proven track record for building ML / AI systems architecture, RAG and multi-agent systems
Deep understanding of transformer models (Huggingface, SentenceTransformers)
Experience with efficiently fine-tuning large language models (LLMs) with LoRA, QLoRA
Knowledge of model optimization techniques (quantization, pruning, distillation)
Experience with multi-modal dataset preparation and quality improvement
Multi-lingual NLP, and cross-lingual transfer learning
Familiarity with language-specific text processing (tokenization, normalization)
Deployment of resource intensive models and scalable AI systems
Monitoring model performance in production and detecting drift
Distributed training (DDP, FSDP, mixed-precision)
Nice-to-have
Hands on experience with open-source LLMs (Gemma, DeepSeek, Llama, GPT-OSS), Building RAG systems, multi-agent systems, and utilizing LLM APIs and vector databases (Pinecone, ChromaDB, FAISS, Milvus), Knowledge of LLM Orchestration Frameworks: LangChain, LangGraph, Llama Index
How to apply
You can submit your application on the company's website, which you can access by clicking the „Apply on company page“ button.
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