딥엑스에서 Generative AI 엔지니어를 채용합니다. LLM/VLM 등 생성형 AI 모델을 엣지 환경에 최적화하고, NPU 하드웨어와 프레임워크를 연동하는 핵심 역할을 수행합니다. PyTorch, C/C++, AI 컴파일러(LLVM/MLIR) 역량이 필수입니다. 세계 최고 수준의 NPU 기술을 함께 만들어갈 분을 찾습니다.
DEEPX is a forward-thinking Series D startup architecting the infrastructure for the Physical AI era.
By delivering the world’s most energy-efficient NPU technology, we are solving the critical power and heat challenges of Generative AI to bring super-intelligence to every device, everywhere.
Our global leadership is validated by our record-breaking recognition as a multi-year CES Innovation Award honoree (2024 & 2026) and being named the 2024 Frost & Sullivan Company of the Year in the NPU sector. With an enterprise value approaching 1 trillion KRW, DEEPX offers a unique pre-IPO
opportunity to join a market leader defining the new industry standard for the $70B AI semiconductor market.
We are currently scaling toward mass production of our flagship DX-M1 (Samsung 5nm) with over 50 global projects scheduled, while engineering next-generation 2nm solutions to support 100B parameter Large Language Models (LLM) at the edge. ☞ Link
★ If you want to be part of world-class innovation? Please talk with us.
★Explore our journey: The DEEPX White Paper ☞ Link
At DEEPX, Generative AI Specialists are responsible for researching all state-of-the-art technologies needed to bring generative AI models (e.g., LLMs, diffusion models) to edge computing environments.
This role focuses on bridging the gap between high-level AI frameworks and DEEPX NPUs. You will be responsible for optimizing complex generative AI models for scalable and efficient inference on edge devices, supporting various frameworks such as PyTorch Native, vLLM, PyTorch Export, Llama.cpp, and ExecuTorch.
The role requires an in-depth understanding of inference model architectures, AI compilers, and hardware characteristics. You will collaborate closely with the Deep Learning Team and other AI software development teams to commercialize generative AI through seamless integration with edge devices.
If you are passionate about shaping the future of generative AI on edge platforms and deeply interested in the full stack from model architecture to compiler optimization, we invite you to join us on this meaningful challenge at DEEPX.
□ Analyze and profile SOTA generative AI models(LLMs, VLMs, VLAs) focusing on edge inference and global trends.
□ Integrate and support various AI inference frameworks(PyTorch Native, vLLM, PyTorch Export, Llama.cpp, ExecuTorch) to run efficiently on DEEPX NPUs.
□ Optimize generative AI model architectures for deployment, leveraging DL compiler technologies (e.g., LLVM, MLIR).
□ Develop and improve model compression techniques (e.g., Quantization, Pruning) tailored for generative AI on edge devices.
□ Implement system-level optimizations to maximize inference performance on DEEPX hardware platforms.
□ Deep understanding of generative AI model architectures(LLM, VLM, VLA) and the end-to-end inference pipeline.
□ Practical experience and strong proficiency with modern AI frameworks and execution environments (PyTorch, vLLM, Llama.cpp, ExecuTorch).
□ Solid understanding of AI compilers(LLVM, MLIR) and how models are translated and optimized for hardware.
□ Fundamental understanding of NPU or AI accelerator hardware characteristics.
□ Proficiency in Python programming and strong C/C++ skills for framework and compiler integration.
□ Strong logical thinking and evidence-based communication skills.
□ Master’s or Ph.D. degree in Computer Science, Machine Learning, Computer Engineering, or related fields.
□ Hands-on experience developing or optimizing pre-training/inference engines for large language models.
□ Deep expertise in AI compiler infrastructures (LLVM, MLIR) or custom graph compilers.
□ Proven track record of deploying and optimizing AI models directly onto edge devices or NPUs.
□ Proficiency in at least one DNN model optimization technique (Quantization, Pruning, Knowledge Distillation, etc.).
□ Publications or presentations at top-tier AI conferences (e.g., NeurIPS, CVPR, AAAI, EMNLP).
□ Recognition in AI competitions or leaderboard rankings.
□ Application Review - (Phone Interview) - Technical Interview - Organizational Culture Fit Interview - CEO Interview - Reference Check / Compensation Discussion
※ The recruitment process may vary depending on the position and application content.
※ Candidates with less than 3 years of experience are required to submit their academic transcripts.
□ Full-time (3-month probationary period with 100% compensation)
□ Monday to Friday, 9:00 AM – 6:00 PM (Lunch break: 12:00 PM – 1:00 PM)
□ If any false information is found in the application or onboarding documents, the job offer may be withdrawn even after confirmation.
□ A 3-month probationary period applies after joining, with no reduction in salary or benefits.
□ 모든 정규직 입사자에게 연봉 수준의 스톡옵션 부여
□ 최신 사양 장비 및 최고의 근무 환경 제공 (최신 노트북, 높낮이 조절식 스탠딩 데스크, 모니터암, 듀얼모니터 등 제공)
□ 점심식사 + 아침 & 저녁식사 지원
□ 스낵, 아이스크림, 음료 등 사내 카페 무제한 간식 제공
□ 사우나가 포함된 피트니스 비용 지원
□ 연 1회 종합건강검진 지원 (배우자 포함)
□ 생일, 결혼기념일, 크리스마스이브 축하금 지급 및 조기퇴근 제공
□ 설/추석 명절 상여금 지급
□ 축하와 위로를 위한 경조휴가 및 경조금 지원
