Senior DFT Methodology - Data Analytics and Applied AI Engineer

Job Title

Senior DFT Methodology - Data Analytics and Applied AI Engineer

Role Summary

Senior engineer on the Design-for-Test (DFT) Methodology team focused on pre-silicon and post-silicon data analytics, visualization, modeling, and applied AI for DFT problems. The role designs data pipelines and analytics to support verification, post-silicon validation, and DFT methodology development for next-generation products.

Experience Level

Senior — typical experience guidance: BSEE with 5+ years, MSEE with 3+ years, or PhD with 1+ year (or equivalent practical experience).

Responsibilities

Primary responsibilities include building analytics and data infrastructure to enable DFT engineering decisions and driving applied-AI solutions in the DFT domain.

• Develop and maintain data pipelines and ETL processes for DFX/DFT engineering data ingestion and processing.
• Create visualizations, analytical reports, and models to extract insights from pre- and post-silicon data.
• Design scalable, fault-tolerant distributed database and storage solutions for large engineering datasets.
• Collaborate with cross-functional teams (execution, analytics, data science, product) to define data requirements and ensure data quality and consistency.
• Apply algorithm design, statistical analysis, and applied AI methods to solve DFT and EDA-related problems.
• Develop and deploy DFT methodologies leveraging Gen AI solutions for next-generation products.
• Mentor and guide junior engineers on test design trade-offs, cost, and quality considerations.

Requirements

Must-have technical skills and experience required for the role; nice-to-have items are listed separately.

• Must-have: Strong experience with SQL, ETL, and data modeling.
• Must-have: Hands-on experience with public cloud platforms (AWS, Azure, or GCP).
• Must-have: Experience designing and implementing scalable, fault-tolerant distributed database/storage solutions; performance tuning and capacity planning for large workloads.
• Must-have: Proficiency with statistical tools and methods for data analysis and deriving engineering insights.
• Must-have: Strong programming/scripting skills (examples: Python, C++, Perl, Tcl).
• Must-have: Excellent written and verbal communication skills and ability to work cross-functionally.
• Nice-to-have: Experience applying AI/ML to EDA problems and building production data pipeline or database architectures for real-world systems.
• Nice-to-have: Proven ability to lead technical efforts and influence teams in a dynamic environment.

Education Requirements

Degree guidance provided: BSEE (or equivalent practical experience) with ~5+ years, MSEE with ~3+ years, or PhD with ~1+ year. Relevant fields mentioned include low-power DFT, data visualization, applied machine learning, and database management. Equivalent professional experience is explicitly accepted.

About the Company

Company: NVIDIA

Headquarters: Santa Clara, California, USA

NVIDIA is a global leader in accelerated computing, renowned for its innovative solutions in AI and digital twins that transform diverse industries. The company specializes in networking technologies, providing end-to-end InfiniBand and Ethernet solutions for servers and storage that optimize performance and scalability. NVIDIA serves sectors such as high-performance computing, enterprise data centers, and cloud computing, constantly reinventing its products and services to stay ahead in the market.