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Описание вакансии
Текст:
TL;DR
AI Engineer Intern (AI): Building and evaluating agentic AI systems for gaming and platform use cases with an accent on LLMs, retrieval-augmented generation, agent orchestration, and model adaptation. Focus on designing multi-step agents, optimizing retrieval pipelines, preparing datasets, and benchmarking system performance, latency, and reliability.
Location: Singapore
Company
Razer develops gaming products and platforms and operates with a global, gamer-focused mission.
What you will do
- Design, prototype, and evaluate agentic AI systems on an internal AI platform.
- Implement agent components including planning logic, tool usage, memory, and multi-step reasoning.
- Develop and optimize RAG pipelines using embeddings and vector databases.
- Prepare datasets and experiment with LLM fine-tuning and adaptation techniques such as instruction tuning and LoRA.
- Integrate third-party AI services and contribute to internal tooling, frameworks, and workflows.
- Benchmark, test, debug, and improve model and system performance, latency, and reliability.
Requirements
- Currently pursuing a degree in Computer Science, AI, ML, or a related technical field.
- Strong Python programming skills and familiarity with software engineering fundamentals.
- Basic understanding of large language models and prompt engineering.
- Familiarity with at least one LLM API or open-source LLM, such as OpenAI, Claude, Gemini, or LLaMA.
- Exposure to or interest in RAG pipelines, agent frameworks, ML workflows, NLP, LLMs, or agent-based systems.
- Coursework, research, personal projects, or hackathon experience involving prompt engineering, embeddings, vector databases, or model adaptation.
Nice to have
- Experience with LangChain or LlamaIndex.
- Experience integrating speech, vision, or agent framework services.
Culture & Benefits
- Full-time internship with hands-on exposure to production-oriented AI engineering.
- Collaboration with AI Engineers, Platform Engineers, and DevOps teams.
- Learning opportunities across the full AI development lifecycle.
- Inclusive and respectful workplace with reasonable accommodations where needed.
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