AI Engineer Intern

Razer (Asia-Pacific) Pte. Ltd

Singapore

Presencial

SGD 17.000 - 23.000

A tiempo parcial

14 días+

Una candidatura completa en un minuto

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Descripción de la vacante

Razer (Asia-Pacific) Pte. Ltd. invites applications for an AI Engineer Intern within the Agentic AI Pod.

You will work with senior AI engineers to design, prototype, and evaluate agentic AI systems on Razer’s internal AI platform, gaining hands-on experience with LLMs, RAG, agent orchestration and model adaptation across real-world gaming use cases. You will help build autonomous AI agents, participate in data preparation and experimentation, and learn production‑oriented AI engineering

Formación

  • Pursuing a degree in Computer Science, AI, ML, or a related technical field.
  • Strong programming skills in Python.
  • 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.

Responsabilidades

  • 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.

Conocimientos

Python
LLMs
Prompt engineering
NLP
Agent frameworks
LangChain
LlamaIndex
Vector databases
OpenAI APIs
LLM APIs

Educación

CS/AI/ML degree

Herramientas

LangChain
LlamaIndex
OpenAI APIs

Descripción del empleo

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

As an AI Engineer Intern within the Agentic AI Pod, you will work closely with experienced AI Engineers to help design, prototype, and evaluate agentic AI systems on Razer’s internal AI platform. This internship offers hands‑on exposure to modern AI stacks involving LLMs, retrieval‑augmented generation (RAG), agent orchestration, and model adaptation, applied to real‑world gaming and platform use cases. You will contribute to building and improving autonomous and semi‑autonomous AI agents, gaining experience across the AI development lifecycle—from data preparation and experimentation to system integration and evaluation—while learning best practices in scalable, production‑oriented AI engineering.

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? 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 do the work and achieve the biggest wins. 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.

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