BRIDGELYT · RESEARCH & OPPORTUNITIES
퓨리오사AI Software Engineer, Build Systems & Release Infrastructure
퓨리오사AI Software Engineer, Build Systems & Release Infrastructure — Seoul. 담당 업무·지원 자격·마감일과 공식 지원 링크를 확인하세요.
진행·예정 · 출처에서 확인한 정보이며 최종 조건은 공식 원문을 확인하세요.
한 줄 요약
퓨리오사AI Software Engineer, Build Systems & Release Infrastructure — 퓨리오사AI · Seoul. 현재 상태: 진행·예정.
정보 갱신일 2026-10-21
조건·일정 확인
- 기관·대학
- 퓨리오사AI
- 지역·근무지
- Seoul
- 학력
- 학사 이상
담당 업무
- Designs and maintains the build systems and toolchains across a polyglot codebase (Cargo, CMake, Python packaging), producing reproducible, hermetic builds across supported platforms.
- Owns the release engineering process for the various packages that make up the Furiosa SDK — versioning schemes, release branching, tagging, changelog generation, and coordinated release cuts across multiple interdependent packages.
- Manages dependency alignment across the SDK's interdependent native components, Python packages, and runtime libraries — defining version constraints and compatibility policy so releases assemble cleanly.
- Builds and operates packaging and distribution pipelines for publicly distributed artifacts — Python wheels (PyPI), APT/RPM packages, and Docker images — including Docker image builds, versioned tagging, signing, metadata, and package repository and container registry maintenance.
- Designs and manages major, minor, and hotfix release workflows, including release planning, stabilization, backports, validation, and end-of-life processes.
- Develops CI automation for build, test, integration, and release, with a focus on build correctness, artifact integrity, caching, and fast, reliable release validation.
- Resolves OS- and platform-specific build issues and upstreams fixes to the open-source community where appropriate.
지원 자격
- Bachelor's degree in Computer Science or equivalent work experience.
- 3+ years in build or release engineering, developer infrastructure, or systems software with significant build and packaging responsibility.
- Strong proficiency in Python and shell scripting (e.g., Bash) for automation.
- Hands-on experience with build systems across compiled and interpreted languages (e.g., Cargo, CMake, Make, Bazel) and with C/C++, Rust, and Python toolchains.
- Fluency with Git and experience setting up and maintaining continuous integration systems.
우대 사항
- Active contributor to the build/release and CI/CD systems of a real-world software project
- Experience with Python packaging and distribution (wheels, manylinux, PyPI) and native extension builds (PyO3, pybind11, or C extensions).
- Experience maintaining APT/RPM repositories and OS package distribution.
- Experience managing reproducible builds, artifact and version management, and dependency resolution across many interdependent packages.
- Experience designing and operating CI/CD with GitHub Actions or similar, including build caching and matrix builds.
- Experience releasing software for GPUs or other accelerator devices, including hardware-dependent build and test pipelines.
- Familiarity with static analysis, code coverage, supply-chain/vulnerability scanning, and artifact signing.
- Experience building across multiple operating systems and distributions (e.g., Ubuntu, CentOS/RHEL).
- talent@furiosa.ai
공식 출처와 다음 단계
공식 원문 확인원천 정보 갱신: 2026. 10. 21. PM 5:06
본문에 없는 자격·금액·일정은 임의로 보완하지 않습니다. 원문과 담당 기관에서 확인하세요.
도구에서 보기·관심 저장관련 정보
퓨리오사AI 연구·기술직 채용 · 연구·기술직 채용공고 전체 보기
연구·기술직 채용공고 · 진행·예정
퓨리오사AI
Architecture Engineer - NPU의 핵심 아키텍처와 연산 구조를 정의하고 성능을 검증합니다. 최신 LLM 연산 패턴 분석을 통한 NPU Core 설계 성능 모델 및 사이클 레벨 시뮬레이터 개발을 통한 면적·성능·정확도 트레이드오프 분석 컴파일러 팀과 긴밀히 협업하여 HW/SW 통합 실행 모델 설계 권...
연구·기술직 채용공고 · 진행·예정
퓨리오사AI
About FuriosaAI FuriosaAI builds high-performance, high-efficiency AI compute for the Inference Era. Founded in 2017 by veteran semiconductor and AI algorithm engineers, Furiosa...
연구·기술직 채용공고 · 진행·예정
퓨리오사AI
About FuriosaAI FuriosaAI builds high-performance, high-efficiency AI compute for the Inference Era. Founded in 2017 by veteran semiconductor and AI algorithm engineers, Furiosa...
연구·기술직 채용공고 · 진행·예정
퓨리오사AI
Cluster-level serving system, heterogeneous computing system 등 차세대 NPU serving의 굵직한 기술 챌린지를 발굴하고 연구 과제로 정의합니다.