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Position Overview:
We are looking for an experienced Synthesis Methodology Engineer to own and drive RTL synthesis methodologies across our AI SoC development projects. You will be responsible for developing, maintaining, and optimizing synthesis flows, evaluating new EDA tools, and enabling efficient implementation across multiple technology nodes.
You will collaborate closely with Design, Backend, CAD, and EDA vendors to improve design productivity and quality.
Responsibilities:
Qualification/ Requirements:
Job ID: 153302609
Skills:
Regression Analysis, Nvme, Continuous Integration, Pcie, Agile Development, Python Programming, Ocp, NAND flash operation, SSD firmware testing, firmware verification planning, automated build, SSD firmware components, SSD system-level debugging, test coverage analysis, branch management, storage protocols and specifications, NVMe-MI, test automation systems, Git development flow, Reporting
Skills:
Regression Analysis, Continuous Integration, Agile Development, Python Programming, NAND flash operation, SSD firmware testing, firmware verification planning, SSD firmware components, SSD system-level debugging, test coverage analysis, branch management, Automated build, test development automation, test automation systems, Git development flow, Reporting
Skills:
synopsys primetime , Ecos, Cadence Genus, EDA Tools, Physical Design, Fusion Compiler, Placement, Innovus, floorplanning, ICC2, Cadence Tempus, Timing Closure, noise analysis, Synopsys Design Compiler, RTL-to-gate synthesis
Skills:
Java, Typescript, Matlab, Python, Javascript, AI Agent system performance profiling, RAG pipelines, chatbots, copilots, context engineering, LLM powered agent systems, containerized deployments, prompt design
Skills:
Java, Golang, Cassandra, Bash, HBase, Redis, Terraform, Kubernetes, Python, Airflow, Step Functions, GitOps, Cadence, Temporal, ArgoCD