AI Engineering Jobs in South Korea
There are 76 open AI Engineering jobs in South Korea on freehire right now. 7 of them were posted recently. The skills employers ask for most often are ai, llm and python.
Most requested skills
- ai 97%
- llm 68%
- python 51%
- machine-learning 49%
- api 34%
- pytorch 34%
- rag 34%
- agentic-ai 26%
How the work is done
- Hybrid 14 · 18%
- Onsite 5 · 7%
- Remote 3 · 4%
Visa sponsorship offered in 81% of the 26 postings that state a position on it.
Seniority
- Intern 8
- Senior 8
- Lead 2
- Staff 2
- Junior 1
Who is hiring
- 51-200 employees 16
- 11-50 employees 14
- 501-1000 employees 12
- 1000+ employees 10
[인턴] [NetsPresso] R&D AI Engineer (Model Representation팀)
R&D intern on Nota’s AI team optimizing models for deployment on edge devices using PyTorch, ONNX, and frameworks like ExecuTorch/TensorRT.
[인턴] [NetsPresso] R&D AI Research Engineer (XPU Enabler팀)
Research and develop quantization, pruning, and inference optimizations for LLM/VLM and MoE models to run efficiently on GPUs and NPUs.
AI Automation Engineer 5년 이상
Build AI-driven automation tools and workflows on GCP to streamline operations, analyze data, and deploy LLM-powered agents that help teams focus on high-impact decisions.
LLM 인프라 및 서빙 엔지니어
Builds and maintains LLM training, fine-tuning, and inference pipelines on AWS using PyTorch, vLLM, and FastAPI to power a healthcare platform’s AI features.
AI Software Engineer - Self-driving Laboratory
Build full-stack software for an AI-driven lab that designs experiments, automates lab robots, and integrates AI models and equipment into a production-ready platform.
AI LLM 개발자
Builds AI-native services using LLM agents and RAG pipelines, implementing FastAPI backends, tool-calling loops, and vector-DB retrieval for autonomous cloud operations.
[인턴] AI Research Engineer - Agents & Workflows
Build and optimize AI agents and multi-step workflows using LLMs to solve real business problems like technical drawing search and insurance claims automation.
AI Research Engineer - Agents & Workflows
Designs and builds AI agent systems that automate complex workflows—like searching 3D/2D drawings or processing insurance claims—using LangChain/LangGraph and LLMs to deliver high-quality, automated solutions.
[인턴] AI Research Engineer - OCR
Research and fine-tune OCR models to handle rotated text, math symbols, and multilingual documents for manufacturing blueprints and medical forms, then serve the models in a SaaS environment.
AI Research Engineer - OCR
Build and fine-tune OCR models to recognize rotated text, math symbols, and multilingual documents for manufacturing blueprints and medical forms.
ML엔지니어(NLP·LLM)
Build and maintain an NLP/LLM pipeline that extracts entities from financial news and disclosures, links them to a financial ontology, and powers RAG/Graph RAG features for evidence-backed answers in a securities trading platform.
LLM Application Engineer
Engineer LLM-powered applications, build retrieval pipelines with vector DBs, design agent workflows, and optimize model quality, latency, and cost.
LLM Application Engineer
Build and ship LLM-powered AI agent workflows that orchestrate multi-step tasks, integrate tools, and turn probabilistic model outputs into reliable user experiences.
AI Engineer (3년 이상)
Build and deploy agentic AI workflows for legal SaaS, using FastAPI backends and LLM tooling to automate contract review and legal research.
AI Engineer
Build AI agents and MCP servers that let LLMs autonomously use internal financial data; optimize GPU/CPU and storage for high-performance AI workloads; and implement end-to-end MLOps pipelines with RAG over knowledge graphs.
LLM/Agent Engineer (과/차장급)
Build and lead a multi-agent LLM system using LangGraph to automate complex workflows for enterprise clients in marketing and e-commerce.
AI Engineer 전문연구요원 [병역특례]
Develops AI/ML models for real-time tire and road condition monitoring using sensor data (CAN, IMU, TPMS) to enable adaptive driving safety features; focuses on edge computing deployment and model optimization for embedded systems.
[인턴] AI Research Engineer (4급 보충역 병특 가능)
Develops AI models for safety applications (e.g., surveillance, quality inspection, deepfake detection) using PyTorch/TensorFlow, focusing on vision-based algorithms like object detection and anomaly detection. Builds MLOps pipelines and explores generative AI for synthetic data generation.
[연구개발] AI Research Engineer (4급 보충역 병역특례/산업기능요원)
Develops AI models for safety applications (e.g., surveillance, quality inspection, deepfake detection) using PyTorch/TensorFlow, focusing on vision-based algorithms like object detection and anomaly detection. Builds MLOps pipelines and explores generative AI for synthetic data generation.
[인턴] AI Engineer
Build scalable data lakehouse pipelines and agentic AI systems that transform unstructured industrial data (CAD, PDF, images) into structured datasets for VLM/LLM training and multi-agent simulations.