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 :

Key Responsibilities

Assist in designing and implementing agentic AI components, such as planning logic, tool usage, memory, and multi-step reasoning

Support the development and optimization of Retrieval-Augmented Generation (RAG) pipelines using embeddings and vector databases

Help prepare datasets and experiment with LLM fine-tuning or adaptation techniques (e.g., instruction tuning, LoRA)

Contribute to internal tooling, frameworks, or workflows for LLM-driven agents

Integrate and experiment with 3rd-party AI services (LLMs, speech, vision, or agent frameworks)

Participate in benchmarking and evaluation of models, prompts, agent behaviors, and retrieval strategies

Assist with testing, debugging, and improving system performance, latency, and reliability

Collaborate with AI Engineers, Platform Engineers, and DevOps teams while learning industry best practices

Stay up to date with emerging trends in agentic AI, LLMs, and RAG systems

Technical Skills

Students pursuing a degree in Computer Science, AI, ML, or a related technical field are welcome to apply

Strong programming skills in Python and familiarity with software engineering fundamentals

Basic understanding of large language models (LLMs) and prompt engineering concepts

Familiarity with at least one LLM API or open-source LLM (e.g., OpenAI, Claude, Gemini, LLaMA)

Exposure to or interest in RAG pipelines, agent frameworks, or ML workflows

Willingness to learn and experiment with modern AI tools and frameworks (e.g., LangChain, LlamaIndex)

Coursework, projects, or research related to NLP, LLMs, or agent-based systems

Experience from academic, personal, or hackathon projects involving: Prompt engineering, Vector databases or embeddings, Fine-tuning or adapting ML models

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?

Job Requirements