NPU Software Engineer Compiler
South Korean AI semiconductor and infrastructure company building inference accelerators, servers, racks, and software for production-scale AI deployment.
Funding history
Investors
About Rebellions
Rebellions develops purpose-built AI inference hardware and an accompanying software stack. Its current offerings include the Rebel100 accelerator and deployable RebelServer, RebelRack, and RebelPOD systems, designed for energy-efficient data-center inference.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will design and develop a compiler stack for accelerating deep-learning models on NPU products. You will architect frontend and backend compiler components, implement optimization strategies, and evaluate core-level and system-level functionality with hardware and system-software engineers.
Requirements
- Master’s degree or higher in Computer Science, Electrical Engineering, or a related field.
- Knowledge of compiler architecture, transformation passes, optimization, scheduling, memory allocation, and backend code generation.
- Analysis, troubleshooting, and debugging skills.
- C++ and Python proficiency.
- Experience developing and maintaining production-level software systems.
- Experience with deep-learning inference on NPU, GPU, or mobile application processor platforms.
- Knowledge of LLM inference, memory management, and high-throughput generation.
- Experience with parallel programming and low-level kernels for AI accelerators or GPUs.
- Knowledge of programming languages, compilers, or computer architecture.
Responsibilities
- Design and develop a compiler stack for NPU products.
- Architect and implement production-grade frontend and backend compilers.
- Implement compiler functionality and optimization strategies.
- Evaluate and validate core-level and system-level functionality.
Hiring Process
Application review → online interview → onsite interview with assessment → culture-fit interview → compensation discussion → final decision.