Job Description:
We have developed a comprehensive intra-organizational communication platform that includes Meet services, conferencing, task management, and other team collaboration tools.
We are now expanding this infrastructure with artificial intelligence technologies to transform it into an intelligent and integrated system that elevates team productivity and user experience.
To support this vision, we are looking for an AI Engineer experienced in language models, speech technologies, and knowledge management to join us in designing and developing the next generation of organizational agents, RAG systems, and data analysis tools.
Responsibilities
- Design and implement a Knowledge Management System (KMS)
- Develop and fine-tune speech models (TTS, STT)
- Design and deploy intelligent agents based on language models capable of task automation, decision-making, and user/system interaction
- Build and optimize RAG pipelines for real-time access to internal and external data
Required Skills
- Solid understanding of LLMs, embeddings, and RAG pipelines
- Experience in prompt engineering for agent development
- Familiarity with Docker and Linux environments
- Strong knowledge of PyTorch for model development and evaluation
- Familiarity with asynchronous programming, multi-threading, and multi-processing concepts
- Proficiency in Python and FastAPI framework
Preferred Skills
- Familiarity with LangChain, Hugging Face, or VLLM
- Experience with Airflow or MLflow tools
- Experience in fine-tuning language models or optimizing open-source models using techniques such as Full Fine-tuning, LoRA / QLoRA, PEFT, or Domain Adaptation
Personal Qualities & Work Culture
- Analytical and structured problem-solving mindset
- Passionate about continuous learning and practical R&D
- Strong collaboration and communication skills
- Understanding of back-end development concepts
Benefits
- Opportunity to learn and work with the latest AI technologies
- Be part of a challenging, creative, and impactful project
- Dynamic, friendly, and research-oriented work environment
- Rapid growth potential and collaboration with a multidisciplinary team