Generative AI Intern
Razer Open · verified Oct 22, 2026 At a glance
Junior AI Engineering role at Razer. Singapore Razer AI Center · full-time.
Pay not stated AI Engineering salary
aimlroles summary, based on the employer's posting.
What you'll do
- Prepare and check datasets used to fine-tune and assess language models
- Adapt language models with LoRA, supervised fine-tuning and preference-optimization methods
- Help run distributed training experiments with PyTorch, Hugging Face, Ray or DeepSpeed
- Compare model quality, response speed, memory demands and training results
- Study quantization and distillation options, then analyze experiments and record what you find
What you bring
- You are working toward a bachelor's or master's degree in computer science, AI, data science or a related area
- You can code in Python and have used either PyTorch or TensorFlow
- You understand machine learning, deep learning and Transformer models
- You can commit to an internship lasting at least sixteen weeks
Who this fits
This junior internship suits a student looking for hands-on work with language-model tuning, evaluation and training experiments. The role is based at the Razer AI Center in Singapore and requires a commitment of at least sixteen weeks.
From the employer
Joining Razer will place you on a global mission to revolutionize the way the world games. Razer is a place to do great work, offering you the opportunity to make an impact globally while working across a global team located across 5 continents. Razer is also a great place to work, providing you the unique, gamer-centric #LifeAtRazer experience that will put you in an accelerated growth, both personally and professionally.
Job Responsibilities :
Join our AI Software team as a Generative AI Intern and help develop and optimize large language models for intelligent and agentic AI applications. You will work on dataset preparation, model fine-tuning, evaluation, and training optimization.Key Responsibilities
• Prepare and validate datasets for model fine-tuning and evaluation.
• Fine-tune language models using techniques such as LoRA, supervised fine-tuning, and preference optimization.
• Support distributed training and experimentation using PyTorch, Hugging Face, Ray, or DeepSpeed.
• Benchmark model quality, latency, memory usage, and training performance.
• Explore optimization techniques such as quantization and model distillation.
• Analyze experimental results and document findings.
Learning Objectives
• Gain hands-on experience in fine-tuning and evaluating large language models.
• Learn practical concepts in distributed training and GPU-based computing.
• Understand dataset preparation, model optimization, and experiment tracking.
• Build experience with production-oriented Generative AI workflows.
Candidate Requirements
• Pursuing a Bachelor’s or Master’s degree in Computer Science, AI, Data Science, or a related field.
• Proficient in Python and familiar with PyTorch or TensorFlow.
• Knowledge of machine learning, deep learning, and Transformer models.
• Familiarity with Hugging Face, distributed computing, or Linux is advantageous.
• Analytical, detail-oriented, and motivated to learn.
• Available for a minimum of 16–20 week internship.
Pre-Requisites :
Razer is proud to be an Equal Opportunity Employer. We believe that diverse teams drive better ideas, better products, and a stronger culture. We are committed to providing an inclusive, respectful, and fair workplace for every employee across all the countries we operate in. We do not discriminate on the basis of race, ethnicity, colour, nationality, ancestry, religion, age, sex, sexual orientation, gender identity or expression, disability, marital status, or any other characteristic protected under local laws. Where needed, we provide reasonable accommodations - including for disability or religious practices - to ensure every team member can perform and contribute at their best.
Are you game?