Frontier AI Intern: Embodied, Healthcare & Multimodal

Amber Group; Hong Kong; On-site; HKD 201,000 - 268,000; Full time

Benefits offered by this job

Competitive internship compensation

Long-term collaboration / full-time 가능

Job summary

Amber Group offers a premier AI internship opportunity in Hong Kong for students in CS/AI/related fields. You will research frontier AI projects, analyze data quality and model performance, and contribute to PoC validation across data processing, training, tuning, and deployment.

The role emphasizes hands-on AI execution, collaboration with university labs and startups, and real-world impact, with potential for long-term collaboration or conversion based on performance.

Qualifications

• Current undergraduate, master’s, or PhD students in Computer Science, AI, Robotics, Automation, Electrical Engineering, Biomedical Engineering, Data Science, or related fields.
• Hands-on experience with AI projects across data processing, model training, tuning, evaluation, and deployment.
• More than paper reproduction or benchmark running — we value candidates who have used AI to solve concrete problems.
• Availability of around 4 days per week for at least 3 months is preferred.

Responsibilities

• Research and analyze frontier AI projects, including technical approaches, data quality, model performance, and real-world feasibility.
• Participate in PoC validation for real application scenarios, including data processing, model training/fine-tuning, evaluation, and deployment testing.
• Collaborate with university labs, early-stage startup teams, and industry partners to move AI technologies from demo to real-world use.

Skills

AI projects

Data processing

Model training

Tuning & evaluation

Deployment testing

Education

Undergrad/Master/PhD student in CS/AI/Robotics/Engineering

Tools

GitHub

HuggingFace

Kaggle

Job description

Amber Group offers a premier AI internship opportunity in Hong Kong for students in CS/AI/related fields. You will research frontier AI projects, analyze data quality and model performance, and contribute to PoC validation across data processing, training, tuning, and deployment.

The role emphasizes hands-on AI execution, collaboration with university labs and startups, and real-world impact, with potential for long-term collaboration or conversion based on performance.