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Mirafra Technologies - SoC Emulation Engineer - System Verilog

Mirafra Technologies
6 - 9 Years
Multiple Locations

Posted on: 11/08/2026

Job Description

Key Responsibilities :

- Build, compile, and deploy GPU SoC emulation models on Synopsys ZeBu platforms.

- Perform design partitioning and mapping for large GPU subsystems, including shader cores, compute units, memory controllers, and interconnects.

- Optimize emulation models for high-bandwidth and concurrency-intensive workloads.

- Debug issues across RTL, compilation, elaboration, and runtime phases.

- Perform initial debug triage and root-cause analysis of test failures.

- Support GPU software bring-up, including firmware, drivers, and kernel integration.

- Enable and debug graphics and compute workloads such as OpenGL and Vulkan.

- Collaborate with Architecture, RTL, Design Verification, and Software teams.

- Drive emulation performance tuning, stability, and turnaround-time improvements.

- Develop automation for build, regression, and emulation workflows.

Required Skills & Experience :

- Bachelor's/Master's degree in Electronics, Electrical, Computer Engineering, or related field.

- 6-9 years of experience in SoC emulation, verification, or related semiconductor domains.

- Strong hands-on experience with Synopsys ZeBu and ZeBu build flows.

- Strong knowledge of Verilog/SystemVerilog.

- Understanding of GPU architecture, including parallel pipelines, scheduling, caches, memory controllers, and memory bandwidth.

- Experience with emulation model build, compilation, debug, and synthesis constraints.

- Strong debugging and problem-solving skills.

- Experience with scripting using Python, Tcl, Shell, or Perl.

Preferred Skills :

- Experience with GPU graphics pipelines or AI accelerators.

- Exposure to Cadence Palladium or Siemens Veloce.

- Knowledge of Vulkan/OpenGL.

- Linux, firmware, or driver bring-up experience.

- Understanding of memory subsystem debugging and performance bottlenecks.

- Experience automating build and regression flows.

Key Deliverables :

- Stable and high-performance GPU emulation models.

- Reduced compile and runtime turnaround time.

- Efficient debugging and triaging of GPU workloads and test failures.

- Automated and scalable emulation build and regression workflows.

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