About the role
We are part of Ericsson Silicon, an engineering unit specializing in the development of state-of-the-art ASICs and FPGAs targeting the latest technology nodes for Ericsson's 5G telecommunication portfolio. This department offers extensive opportunities for career growth, along with access to a vast knowledge base that supports innovation and advancement.
To excel in this high-visibility role, we seek individuals with a background in ASIC IP/ASIC SoC development, DevOps, and CI/CD automation. You will play a crucial role in shaping and optimizing methodologies, EDA workflows, and compute cluster efficiency, ensuring the seamless adoption of industry best practices for high-performance silicon design.
Additionally, this role requires expertise in CI/CD automation, specifically in Jenkins review flows, timed/nightly builds, and release automation. A key focus is on integrating AI/ML techniques to optimize verification flows, improve throughput, and enhance the scalability of compute resources.
What you will do:
• Design and maintain Jenkins review flows, timed/nightly builds, and release automation for silicon development.
• Optimize EDA Workloads throughput and efficiency of compute clusters, ensuring high performance and scalability.
• Develop robust CI/CD pipelines tailored for silicon design and verification.
• Develop, deploy, and support EDA tool flows in Frontend Design & Verification.
• Implement AI/ML-driven automation for job scheduling, resource management, and verification flow optimizations.
• Identify and address inefficiencies in flow, methodology, and tooling for IP/ASIC/SoC environments.
• Collaborate with engineering teams to streamline build, test, and deployment processes.
• Ensure high availability, reliability, and security of CI/CD infrastructure.
Skills you Bring:
We see you have 5+years of experience overall
• Strong expertise in Jenkins, Groovy scripting, and pipeline automation.
• Experience in DevOps for hardware/software co-design, with a focus on silicon development.
• Deep understanding of compute cluster scheduling, resource management, and optimization.
• Hands-on experience with Kubernetes, Docker, and cloud-based CI/CD solutions.
• Knowledge of AI/ML frameworks and their application in workflow optimization.
• Proficiency in scripting languages (Python, Bash, etc.) for automation.
• Familiarity with Git, artifact management, and release engineering best practices.
• Hands-on experience continuous integration methodologies and AI/ML applications in DevOps.
• Effective communication and leadership in distributed engineering teams.
