- Oversee the design, deployment, and management of hardware and software test systems and interfaces for efficient test execution, supporting bench and system validations. Implement best practices to perform QA on the system.
- Collaborate with internal and external teams to define, evaluate, and improve validation toolchains.
- Architect and maintain validation data management and directory structures for data analysis and extraction
- Create and maintain visualization tools tailored to needs of IP validation team, and implement iterative features for effective data exploration and analysis
- Launch data analytics framework and identify key performance indicators by collaborating with various design and validation teams.
- Identify opportunities for modularization and standardization to improve the validation pipeline. Collaborate with cross-functional teams to develop and implement software interfaces to seamlessly transition pre-silicon verification flows to post silicon.
- Follow security measures to safeguard sensitive data and ensure compliance
- Foster collaborative and innovative work culture within the team as well as when working with cross-functional teams.
Minimum Qualifications
Master’s degree or equivalent in EE/CS is required plus 8+ years industry experience.
Preferred Qualifications
The ideal candidate will have the following qualifications:
8+ years of experience in leading, managing and developing validation hardware and software systems to support the validation of AMS or SOC IPs, including automated and modular scalable lab setups and remote testing frameworks.
Deep understanding of both HW and SW needs for the validation of various AMS IPs from on chip to in the system
Hands-on experience with lab equipment (e.g. oscilloscope, signal analyzers, BERT)
Strong programming and scripting skills (e.g., Python, C/C++, MATLAB, LabVIEW, JMP, etc.) for automation and data analysis.
Knowledge of data processing, visualization, and analysis tools (e.g. Jupyter, Pandas, Tableau), and expertise in initiating and implementing data analytics processes
Knowledge of semiconductor technologies, IC design architectures and principals, as well as familiarity with industry EDA tools and simulation setups.
Understanding of machine learning techniques for validation data analytics is a plus.
Strong technical leadership, effective communication, and collaboration skills.
Excellent problem solving and analytical skills with a structured approach to issue resolution.
Meticulous organizational skills.
PhD is preferred