Large Language Model Intern

Razer (Asia-Pacific) Pte. Ltd; Singapore; On-site; SGD 17,000 - 27,000; Full time

Job summary

Razer (Asia-Pacific) Pte. Ltd. invites applicants for an ML internship to train and optimize language models for Razer Software.

You will tackle the full training pipeline—from corpus construction to deployment optimization—and own workstreams end-to-end with guidance from senior data scientists and engineers. You’ll learn practical ML data engineering, model evaluation, and deployment considerations, including latency and memory constraints, while contributing to a real production roadmap in a

Qualifications

• Education: Current Bachelor's, Master's, or PhD student in CS, AI, Data Science, or a related field.
• Must‑have knowledge: LLM training paradigms (pretraining, SFT, LoRA, preference optimization); Transformer/deep learning fundamentals; deployment constraints (latency, memory) shape training decisions
• Must‑have skills: Python; hands‑on PyTorch model training; data engineering for training corpora (cleaning, filtering, dedup, mixing); end‑to‑end experiment running (debugging, hyperparameter tuning, analysis); benchmarking quality/latency/memory
• Nice‑to‑have: Model compression (quantization, distillation), distributed training (multi‑GPU/parallelism), Hugging Face/Accelerate/DeepSpeed, Linux environment
• Screening bar (hard requirement): Demonstrable hands‑on model training/fine‑tuning experience (coursework, research, internship, or open‑source). API‑calling or prompt‑engineering‑only experience does not qualify.

Responsibilities

• Train and optimize language models for Razer Software across the full pipeline — pretraining corpus construction, fine‑tuning, evaluation, and deployment optimization.
• You’ll own discrete workstreams end‑to‑end (design → run → debug → analyze → iterate) on the model powering Razer Software.
• Collaborate with senior data scientists and engineers to align training with production constraints and roadmap.

Skills

Python

PyTorch

Data engineering for training corpora

Experiment automation

Education

Current Bachelor's/Master's/PhD student in CS/AI/DS or related field

Tools

Hugging Face/Accelerate/DeepSpeed

Linux environment

Job description

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

Train and optimize language models for Razer Software, across the full pipeline — pretraining corpus construction, fine-tuning, evaluation, and deployment optimization.

Job Scope

You’ll work with senior data scientists and engineers on the model powering Razer Software, covering the full training pipeline:

• Corpus construction — cleaning, filtering, deduplication, and mixing of training data
• Fine-tuning — SFT, LoRA, and preference optimization runs
• Evaluation — quality, latency, and memory benchmarking against production constraints
• Deployment optimization — compression and quantization experiments for on-device targets

You’ll own discrete workstreams end-to-end (design → run → debug → analyze → iterate) rather than executing isolated tasks handed down by a mentor.

Learning Objectives

By the end of this internship, you will have:

• Hands‑on experience across the full LLM training lifecycle at production scale — not toy datasets
• Practical judgment in data engineering: how cleaning/filtering/mixing decisions propagate into model quality
• The ability to independently run a rigorous ML experiment loop — hypothesize, train, evaluate, diagnose subtle regressions, iterate
• Direct exposure to how deployment constraints, shape training and architecture decisions, including compression, quantization, and distillation tradeoffs
• Mentorship from senior engineers and visibility into how a production roadmap for a shipping AI feature actually gets decided.

Candidate Requirements

Education: Current Bachelor's, Master's, or PhD student in CS, AI, Data Science, or a related field

Must‑have knowledge:

• LLM training paradigms (pretraining, SFT, LoRA, preference optimization); Transformer/deep learning fundamentals; how deployment constraints (latency, memory) shape training decisions

Must‑have skills:

• Python; hands‑on PyTorch model training; data engineering for training corpora (cleaning, filtering, dedup, mixing); end‑to‑end experiment running (debugging, hyperparameter tuning, analysis); benchmarking quality/latency/memory

Nice‑to‑have:

• Model compression (quantization, distillation), distributed training (multi‑GPU/parallelism), Hugging Face/Accelerate/DeepSpeed, Linux environment

Screening bar (hard requirement): Demonstrable hands‑on model training/fine‑tuning experience (coursework, research, internship, or open‑source). API‑calling or prompt‑engineering‑only experience does not qualify.

Strong positives:

• Trained a model from scratch (any scale), multi‑GPU training, model compression/on‑device deployment work, top‑tier publications (CVPR, NeurIPS, ICML, ACL, ICLR, EMNLP, etc.)

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? At Razer, you’ll be at the forefront of the most exciting industry in the world: gaming. As gaming evolves, so does the ecosystem that powers it: hardware, software and services. Guided by our mission “For Gamers. By Gamers.”, we create cutting‑edge products and experiences that define the ultimate gameplay. Staying true to our mission, we’re relentlessly pushing boundaries and leading the charge in AI for gaming, shaping the future of the industry. At Razer, you won’t just witness this evolution; you’ll help drive it. Joining Razer means being part of a global mission to bring gamers closer to the games they love. Whether you’re crafting the next generation of gaming gear or powering our global operations behind the scenes, you’ll take on meaningful work in a truly international, cross‑cultural environment. The journey toward Being Phenomenal isn’t always easy, but gamers excel through teamwork, grit, and problem‑solving. Our people are what make Razer exceptional. Together, we’ll take Razer to even greater heights. Razer is proud to be certified a Great Place to Work® in both the United States and Singapore, and recognized as a Singapore Top Employer by the Top Employer Institute, reflecting our commitment to making your journey here a rewarding one.

Equal Opportunity Employer At Razer, we believe diverse teams build better ideas and a stronger culture. We are committed to providing an inclusive, respectful, and fair workplace for every employee.

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 by the laws of the countries we operate in.

We also provide reasonable accommodations where needed — including for disability or religious practices — so every team member can perform and contribute at their best.