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 Automation Framework Ownership
• Own, maintain, and enhance the end-to-end automation flow used to: • Compile neural networks using the XNNC compiler. • Run generated RTL binaries on Palladium Z3 emulation. • Drive Joules gate-level power analysis.
• Develop and maintain the Python, CSH, and Bash scripts that integrate and orchestrate the flow. • Add support for new AI network configurations, hardware accelerator variants, reference builds, and EDA tool revisions. • Maintain current documentation, patches, reference configurations, and reproducible build instructions. • Identify, debug, and resolve automation, infrastructure, and tool-integration issues across the workflow. Performance and Power Collateral Generation
• Generate complete performance and power collateral for each neural network processed through XNNC. • Collect and summarize: • Cycle count, frames per second (FPS), and memory-bandwidth metrics from XTSC simulation. • End-to-end performance metrics from Palladium emulation. • Dynamic power estimates, including total and memory power, from Joules gate-level analysis.
• Deliver results consistently across reference builds in standard formats, including cycle-count CSVs, power CSVs, and consolidated summary reports. • Validate result quality, consistency, and reproducibility before collateral is shared with stakeholders. Team Enablement and Support
• Serve as the primary internal point of contact for users of the COLLATERAL-AUTO project. • Onboard new users and provide guidance on running the XNNC, Palladium, and Joules workflow. • Debug user runs and triage issues related to environments, scripts, CAD/EDA tools, and flow configuration. • Review performance and power summaries for correctness, completeness, and consistency. • Improve team-wide productivity by creating reusable guidance, troubleshooting documentation, and reliable reference workflows. Required Qualifications Experience
• 10+ years of experience in various embedded software or general software development roles. • 3+ years of experience with AI frameworks, AI network compilation, or related tooling. • Experience with one or more of: TensorFlow, PyTorch, ONNX, Apache TVM, or AI network compilers. Technical Expertise
• Strong Python scripting skills. • Proficiency with CSH and Bash shell scripting. • Working knowledge of JSON and automation-oriented configuration formats. • Understanding of hardware edge-AI accelerators, RTL execution flows, and performance analysis. • Familiarity with debugging complex software, toolchain, and multi-stage automation issues. Education
• Bachelor’s or Master’s degree in Software Engineering, Electronics Engineering, Electrical Engineering, Computer Engineering, or a related discipline. Preferred Qualifications
• Experience using AI-assisted development tools for rapid prototyping and effective technical prompting. • Experience with Cadence tools, including Palladium and Joules, or equivalent EDA/emulation/power-analysis workflows. • Familiarity with IP design platforms, RTL simulation or emulation, gate-level power analysis, and AI accelerator validation. • Strong written communication skills for producing technical documentation, runbooks, and performance/power reports. We’re doing work that matters. Help us solve what others can’t.