MiAO Worlds – Research Scientist Intern

Key Responsibilities 

a. AI and Gaming Research:

i. Participate in multimodal language model application delivery, and first-authored publications at leading workshops, conferences, or journals

ii. Research on AI in game industry production pipelines

b. Agent Development:

i. Assist in the design, development, and testing of advanced AIGC algorithms to generate compelling and high-quality content. Particularly in optimizing model preference alignment with the specific needs of the modern game industry formal logic abstraction.

ii. Research and implement state-of-the-art machine learning techniques to improve algorithm performance and efficiency.

iii. Ideate, develop and compare the performance of agent architectures to maximize model performance or case of use on agentic tasks

c. Dataset Engineering:

i. Assist in designing and implementing subtle prompting strategies and data pipelines, identify and fix edge case behaviors through testing of data generation pipelines

ii. Assist in implement data augmentation strategies and managing data pipelines to ensure high-quality data flow.

iii. Assist in developing evaluations of model behaviors across judgement-based domains.

d. Model Deployment:

i. Support the deployment of AI models into production environments, helping to ensure their scalability and reliability.

Requirements

Education: 

Fresh Grad/Master’s Students in Computer Science, Data Science, or a related field (4th year students, undergraduates or graduate level)

Technical Skills:

a. Background knowledge of Language Model, Agent, or Multimodal Language Model preferred. Primary interest in large language model application delivery, and authored publications at leading workshops, conferences, or journals is preferred.

b. Familiarity with machine learning technology stacks, including core technologies such as PyTorch, LLMs, multimodal systems, Agent systems, and RAG.

c. Problem-solving and analytical mindset: Ability to analyze complex problems, break them down into manageable components, and contribute to the development of innovative machine learning solutions. Strong mathematical and analytical skills are a plus.