Verification Engineer

We are seeking a skilled and experienced Staff Verification Engineer to join our team. The ideal candidate will have extensive experience in verifying designs based on RISC, SIMD, VLIW, or GPU architectures. You will play a key role in developing and reviewing test plans, performing full-chip functional verification, and developing test benches in System Verilog to ensure complete functionality coverage of processor designs.

Key Responsibilities:

• Perform verification of designs based on RISC, SIMD, VLIW, or GPU architecture.
• Develop and review test plans, including estimates and risk analysis, for functional verification of processors.
• Conduct full-chip functional verification and develop comprehensive test benches in System Verilog.
• Ensure complete functionality coverage and identify any verification gaps.
• Implement ULT development using UVM/SV, assembly programming, and parallel programming for design verification.
• Work with the team to develop innovative verification strategies, optimizing resources and meeting organizational goals.
• Collaborate with cross-functional teams to ensure thorough verification of memory subsystems and processor architecture.
• Troubleshoot and debug test benches to address issues and ensure high-quality verification.

Required Skills & Qualifications:

• Extensive experience in verification of designs based on RISC, SIMD, VLIW, or GPU architectures.
• Strong knowledge of ULT development, UVM/SV, assembly programming, and parallel programming.
• Experience in verifying image, video, or graphics-related IPs is a plus.
• Familiarity with AMBA AXI, AHB, and APB protocols.
• Strong experience with Test Bench development, debugging, and problem-solving.
• In-depth understanding of computer architecture, including memory subsystems.
• Excellent strategic planning skills to optimize resources and meet verification goals.

Additional Skills (Nice-to-Have):

• Experience with emulators like Palladium or Zebu.
• Knowledge of FPGA prototyping.
• Familiarity with Automotive ISO 26262 Functional Safety Standards.
• Understanding of GPU/AI/ML processor architecture.

Education:

• Bachelor's or Masters degree in Electrical Engineering, Computer Science, or a related field.