About this role
At Cadence, we hire and develop leaders and innovators who want to make an impact on the world of technology.
Key Responsibilities
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Automation Framework Ownership
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Own, maintain, and enhance the end-to-end automation flow used to:
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Compile neural networks using the XNNC compiler.
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Run generated RTL binaries on Palladium Z3 emulation.
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Drive Joules gate-level power analysis.
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Develop and maintain the Python, CSH, and Bash scripts that integrate and orchestrate the flow.
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Add support for new AI network configurations, hardware accelerator variants, reference builds, and EDA tool revisions.
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Maintain current documentation, patches, reference configurations, and reproducible build instructions.
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Identify, debug, and resolve automation, infrastructure, and tool-integration issues across the workflow.
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Performance and Power Collateral Generation
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Generate complete performance and power collateral for each neural network processed through XNNC.
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Collect and summarize:
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Cycle count, frames per second (FPS), and memory-bandwidth metrics from XTSC simulation.
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End-to-end performance metrics from Palladium emulation.
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Dynamic power estimates, including total and memory power, from Joules gate-level analysis.
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Deliver results consistently across reference builds in standard formats, including cycle-count CSVs, power CSVs, and consolidated summary reports.
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Validate result quality, consistency, and reproducibility before collateral is shared with stakeholders.
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Team Enablement and Support
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Serve as the primary internal point of contact for users of the COLLATERAL-AUTO project.
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Onboard new users and provide guidance on running the XNNC, Palladium, and Joules workflow.
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Debug user runs and triage issues related to environments, scripts, CAD/EDA tools, and flow configuration.
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Review performance and power summaries for correctness, completeness, and consistency.
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Improve team-wide productivity by creating reusable guidance, troubleshooting documentation, and reliable reference workflows.
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Required Qualifications
Experience
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10+ years of experience in various embedded software or general software development roles.
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3+ years of experience with AI frameworks, AI network compilation, or related tooling.
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Experience with one or more of: TensorFlow, PyTorch, ONNX, Apache TVM, or AI network compilers.
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Technical Expertise
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Strong Python scripting skills.
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Proficiency with CSH and Bash shell scripting.
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Working knowledge of JSON and automation-oriented configuration formats.
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Understanding of hardware edge-AI accelerators, RTL execution flows, and performance analysis.
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Familiarity with debugging complex software, toolchain, and multi-stage automation issues.
Education
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Bachelor’s or Master’s degree in Software Engineering, Electronics Engineering, Electrical Engineering, Computer Engineering, or a related discipline.
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Preferred Qualifications
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Experience using AI-assisted development tools for rapid prototyping and effective technical prompting.
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Experience with Cadence tools, including Palladium and Joules, or equivalent EDA/emulation/power-analysis workflows.
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Familiarity with IP design platforms, RTL simulation or emulation, gate-level power analysis, and AI accelerator validation.
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Strong written communication skills for producing technical documentation, runbooks, and performance/power reports.