Senior DFT Methodology - Data Analytics and Applied AI Engineer
NVIDIAJob Title
Senior DFT Methodology - Data Analytics and Applied AI Engineer
Role Summary
The Design-for-Test (DFT) Data Analytics and Applied AI Engineer builds data pipelines, analytics, and AI-driven solutions to support pre-silicon and post-silicon DFT activities. Works within NVIDIA's DFT engineering team to deliver data-driven insights, tooling, and methodologies for complex semiconductor products.
Experience Level
Senior level — role expects senior engineering experience. Posting guidance: BSEE with 5+ years, MSEE with 3+ years, or PhD with 1+ years (equivalent practical experience accepted).
Responsibilities
Key responsibilities include:
- Develop and maintain data pipelines, ETL, and ingestion processes for DFX engineering data.
- Build visualizations, models, and analytics for pre-silicon and post-silicon validation and verification.
- Collaborate with execution, analytics, data science, and product teams to define data requirements and ensure data quality and consistency.
- Apply statistical analysis, algorithm design, and applied AI methods to DFT problems.
- Design and deploy GenAI-enabled DFT methodologies and tooling for next-generation products.
- Design scalable, fault-tolerant storage and distributed database solutions; lead performance tuning and capacity planning.
- Mentor junior engineers on test design trade-offs, cost, and quality.
Requirements
Must-have technical skills and experience:
- Proven experience with SQL, ETL, and data modeling for engineering datasets.
- Hands-on experience with cloud platforms (AWS, Azure, GCP).
- Experience designing and operating scalable, fault-tolerant distributed database/storage solutions and tuning large-scale workloads.
- Strong knowledge of statistical tools for data analysis and insight generation.
- Programming/scripting proficiency in Python, Perl, C++, or Tcl.
- Excellent written and oral communication and the ability to collaborate across teams.
- Ability to tackle hard-to-solve problems in the DFT domain.
Nice-to-have:
- Experience applying AI to EDA-related problems.
- Experience in production data pipeline and database architecture for real-world systems.
- Demonstrated ability to guide and influence engineering teams in a dynamic environment.
Education Requirements
BSEE (or equivalent practical experience) with 5+ years, MSEE with 3+ years, or PhD with 1+ years in a related technical field (for example, Electrical Engineering, Computer Engineering, Computer Science), or equivalent practical experience.
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.
