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Machine Learning Engineer

Bosnia and Herzegovina, North Macedonia, Croatia, Hungary, Spain, Czech Republic, Serbia (Hybrid)

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Join us in shaping the future of media and entertainment by building cutting-edge multilingual transcription systems that power global storytelling. In this role, you’ll tackle complex challenges—from delivering accurate, consistent audio and text transcription across diverse media assets to enabling automatic language and locale detection in real-world scenarios. You’ll work with state-of-the-art LLMs and transformer-based architectures to push the boundaries of multilingual and mixed-language understanding. If you’re passionate about architecting scalable AI solutions and fine‑tuning high‑impact models, we’d love to meet you.

Requirements:   

  • 5+ years of industry experience, 2+ year 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   

   
Required skills:   

  • 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) 

  

Preferred skills:   

  • 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 

 

Machine Learning Engineer

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Machine Learning Engineer

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