Lead development of iJTAG (IEEE 1687) based test solutions, including scan network modeling, instrument access, and test pattern execution. Build APIs and pipelines for Large-scale data ingestion (ATE logs, STIL/WGL patterns) and data processing and visualization dashboards.
Numbers & Facts
Location
San Jose, CA
Description
Lead development of iJTAG (IEEE 1687) based test solutions, including scan network modeling, instrument access, and test pattern execution.
Design and implement DFT methodologies including scan, BIST, and hierarchical access mechanisms.
Build AI/ML features in DFT tools for pattern compaction, failure prediction, and scan-failure root-cause analysis
Develop scalable automation frameworks in Python/C++ and streamline DFT workflows using Tcl/Perl/Shell
Build APIs and pipelines for Large-scale data ingestion (ATE logs, STIL/WGL patterns) and data processing and visualization dashboards
BE/ME Computer Science, Electronics Engineering or related professions with at least 5-8 years working experience in software development
Strong expertise in Scan architectures, compression techniques, fault simulation and coverage metrics
Strong programming expertise in C,C++ or Python and experience in data structures, algorithms, and scalable system design in Linux OS
Hands-on experience in ML frameworks (PyTorch, TensorFlow) and
data handling (Pandas, NumPy)
Knowledge of classification, clustering, anomaly detection and feature engineering for semiconductor/test datasets
Strong attention to details, verbal communication and written skill sets, and ability to work with a highly diverse team-structured environment with positive attitude is mandatory
Ability to work in a fast paced, project oriented, team environment and escalate any critical issues to the senior management.
Desired
Experience in electronic measurements/design, and ATE testing, preferably in the digital and High-Speed application domain
Contributions to test optimization/yield improvement frameworks
Exposure to GenAI/Copilot-style assistants for debugging or automation
Experience working with large silicon datasets (production scale)