AI Engineer

MAIN TASKS & RESPONSIBILITIES
1) Build & Operate AI Platform
Design AI/ML systems (data pipeline, model serving, monitoring, etc.) to ensure stability and scalability.
Deploy and manage AI models in cloud or on-premises environments (any platform; experience with GCP is a plus).
Integrate AI models into Game/App applications (via APIs or in-house frameworks).
2) Develop Generative AI Solutions
Conduct research and fine-tune LLMs (GPT, T5, BERT, etc.) or other generative models (GAN, Diffusion Models…) to build:
AI Chat: Intelligent, multilingual chatbots integrated into mobile applications.
AI Image, AI Audio, AI Video: Integrate AI-generated images, videos, and audio for Creative/Art teams.
AI Agent: Automate processes to enhance internal efficiency (e.g., document classification, report summarization, employee support chatbots).
Research and apply Prompt Engineering, ensuring model outputs are accurate and contextually relevant in a systematic and strategic manner.
3) Optimize MLOps Processes
Set up and maintain CI/CD for AI models, manage versioning for models and data, and continuously monitor performance.
Ensure AI model development follows standards, with the ability to detect and address model drift early.
4) Collaborate on Game/App Product Development
Work with Product Teams, Game Developers, and App Developers to understand requirements, propose, and build AI solutions that meet real-world needs.
Measure and analyze usage metrics (user metrics, model performance) to continuously improve and optimize user experience.
5) Research & Knowledge Sharing
Participate in or lead R&D activities, experimenting with new AI techniques, especially in the Generative AI domain.
Mentor and provide best practices for various teams applying AI.
Stay updated on technology and AI trends to maintain a competitive edge in the global game/app market.
6) Development Opportunities
Potential to lead AI projects, shape AI strategies for product lines, drive technical direction, and manage AI/ML teams.

REQUIREMENTS / EXPERIENCE
1) Foundational Knowledge & Education
Bachelor’s/Master’s degree in Computer Science, Software Engineering, Artificial Intelligence, Mathematics–Informatics, or a related field.
Strong understanding of Machine Learning and Deep Learning methods, as well as data structures and algorithms.
2) Practical Experience
At least 2-3 years of experience in AI/ML; preferably having worked with Generative AI (LLMs, NLP, Chatbots, etc.).
Proficiency with popular AI frameworks such as TensorFlow, PyTorch, Hugging Face, Scikit-learn, or equivalents.
Experience deploying AI models on cloud platforms (AWS, Azure; GCP is a plus), containerization (Docker, Kubernetes), and CI/CD.
3) MLOps & Deployment Skills
Solid knowledge of data pipelines, model monitoring, and model version control.
Ability to optimize costs and resources (GPU, TPU) while ensuring the security and stability of AI systems.
4) Problem-Solving & Communication
Capable of analyzing and proposing AI solutions that bring real value to game/app products and internal processes.
Strong communication and presentation skills; able to collaborate effectively with Product, Development, and Business teams.
Sufficient English proficiency to research documentation, discuss with partners, or read the latest AI papers.
5) Passion for Generative AI
Keen interest in enhancing user experiences through AI and optimizing internal tasks.
Willingness to experiment with new technologies, proactively learn, and creatively tackle complex challenges.