Posting record
Open 12+ days
- Razer's site dates the posting
- Ghostless first sees this listing
- Last checked: still up
How we know
It hasn't been reposted, listed twice, or left up unusually long, and the posting doesn't say it's a talent pool.
Ghostless records the day it first sees a posting, so a repost can't reset its age. This one was already up when Ghostless started tracking Razer, so its true age is longer.
Last checked Nov 3, 2026.
How well do you match?
See how much of this posting your resume shows, and what it's missing.
Upload your resumeWhat it asks of you
- Must be a current student
What the posting discloses
Not stated: Pay, real vacancy, AI screening.
Why these three
Ontario requires postings from employers with 25 or more staff to state the pay, whether the vacancy exists, and whether AI screens applicants.
Some employers add pay only on their own site. Check the original posting before you rule it out.
Skills mentioned
About the role
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?
Something wrong with this posting?