Architect – AI-Powered Performance Verification Automation

Automate verification workflows by building AI/ML-based tools that generate, triage, and analyse performance test cases and results

Develop intelligent agents that can identify performance regressions, root-cause failures, and recommend corrective actions

Integrate LLM-based assistants into existing verification infrastructure to enable natural-language querying of results, specs, and coverage data

Design data pipelines to collect, curate, and label verification data for model training and continuous improvement

Collaborate with verification engineers to understand pain points, define automation priorities, and validate AI-driven solutions against real-world workflows

Establish metrics and dashboards to measure automation impact (cycle time reduction, coverage improvement, engineer productivity)

Stay current with state-of-the-art techniques in generative AI, reinforcement learning, and formal methods as they apply to hardware verification

B.Tech/M.Tech/PhD in Electrical Engineering, Computer Science, or a related field

3+ years of experience in hardware verification, performance validation, or EDA tool development

Strong programming skills in Python; familiarity with C/C++, SystemVerilog/UVM is a plus

Hands-on experience with ML/AI frameworks (PyTorch, TensorFlow, scikit-learn) or LLM APIs (OpenAI, NVIDIA NIM/NeMo)

Understanding of performance verification methodologies (benchmarking, profiling, regression analysis)

Experience with CI/CD pipelines and infrastructure automation