Software Engineer 3년 이상

소개

■ Axion은 AI 기반의 혁신적인 반도체 자동설계 및 최적화 솔루션 개발과 산업 전반에 걸친 AI기반 설계 최적화 소프트웨어를 개발하여 글로벌 반도체 시장 및 다양한 산업 영역의 미래를 선도하는 기업입니다. ■ AI Engine을 통해 반도체 설계 프로세스를 혁신하고 있는 저희와 함께 성장할 열정적이고 창의적인 Engineer를 모집합니다.

주요업무

■ 주요 업무 Design, implement, and tune placement and routing algorithms for transistor-level cell layout generation. Formulate layout constraints (design rules, pin access, symmetry, track assignment) as SAT / SMT / ILP / CP models, or develop custom heuristic solvers. Improve solver performance through search-space pruning, symmetry breaking, incremental solving, and parallelization. Measure and improve quality of results (area, routability, DRC-clean rate) against hand-crafted reference layouts. Build benchmark suites and regression harnesses to track QoR and runtime across solver and rule changes. Work with layout and PDK engineers to translate foundry design rules into solver constraints. Document algorithms and contribute to the tool’s algorithmic roadmap. Explore and implement first-order optimization methods (e.g., PDLP) and hardware-accelerated algorithms to scale solver capabilities for massive layout instances

자격요건

■ 자격요건 ㆍ경력 3년 이상 ㆍ대학졸업(4년)이상 BS / MS / PhD in Computer Science, Operations Research, Mathematics, or a related field with a focus on algorithms, optimization, or scheduling. 3+ years of experience developing optimization, scheduling, or search algorithms in production software, or a PhD with equivalent research engineering depth. Strong C++ with attention to performance and memory; working Python. Solid foundation in combinatorial optimization: ILP / SAT / SMT / CP, graph algorithms, dynamic programming, and local search. Experience profiling and optimizing algorithm runtime and memory on large problem instances. Treats solution quality, runtime, and hardware usage as first-class requirements.

우대사항

■ 우대사항 Experience with EDA placement & routing, layout automation, or VLSI CAD algorithms. Hands-on experience with industrial solvers (Gurobi, CPLEX, OR-Tools, Z3, MiniSat/Kissat), including model tuning. Experience with parallel or distributed search, or solver portfolios. Familiarity with modern large-scale linear programming techniques (e.g., PDLP) and their acceleration via parallel architectures or GPUs (e.g., CUDA). Publications or contest results in optimization, SAT, or EDA (ISPD / ICCAD / DAC contests). Familiarity with semiconductor design rules and standard cell layout.

혜택 및 복지

• 시차 출퇴근 운영 • 점심 식사 제공 • 건강 검진