NPU SDK Software Engineer (AI)

TL;DR

NPU SDK Software Engineer (AI): Own end-to-end SDK user experience for bringing state-of-the-art AI models (LLM, Multi-modal, Vision, Speech) onto hirify.global NPU with an accent on model porting, CI/CD pipelines, framework integration, and developer documentation. Focus on optimizing performance, ensuring numerical parity, designing verification tools, and integrating with Hugging Face, vLLM ecosystems.

Location: hirify.global office in Seongnam-si, Bundang-gu, South Korea (경기도 성남시 분당구 정자일로156번길 6, R-TOWER 3F ~ 8F)

Company

AI hardware company developing Neural Processing Units (NPU) for edge AI inference.

What you will do

• Design, build, and operate CI/CD pipelines to automate SDK release processes
• Port and optimize deep learning models (LLM, Multi-modal) onto hirify.global NPU, analyze bottlenecks, validate against GPU references
• Integrate SDK with open-source ecosystems like Hugging Face Transformers, Diffusers, vLLM
• Design model-feeding frameworks and debugging utilities for functional correctness and stability
• Author developer documentation including API references, tutorials, model matrices, release notes

Requirements

• Master’s degree or above in Computer Science, Electrical Engineering, or related field
• Deep knowledge of CI/CD tools (GitHub Actions, Airflow, Buildkite)
• Strong understanding of deep learning architectures (LLMs, Multi-modal, Vision, Speech)
• Familiarity with PyTorch internals, model customization, graph transformations
• High-performance development in Python and Modern C++ (C++17+)
• Experience with Hugging Face libraries and vLLM integration
• Hands-on with Python and Kubernetes for AI inference workloads

Nice to have

• 5+ years relevant experience
• Model optimization on hardware (CUDA, TensorRT, MLIR, Triton, TVM)
• Scalable ML infrastructure with Docker/Kubernetes
• AI Harness Engineering experience
• Open-source contributions
• Knowledge of JAX or TensorFlow internals

Hiring process

• Document screening > Online interview > On-site interview > Culture-fit interview > Compensation discussion > Final offer
• Process may vary by role and schedule
• Results sent via email