Principal Software Engineer

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.

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