Senior Applied AI and AI Infrastructure Engineer - Chip Design and DFX
NVIDIAJob Title
Senior Applied AI and AI Infrastructure Engineer - Chip Design and DFX
Role Summary
Senior engineer on the Design-for-X (DFX) team applying machine learning and generative AI to chip design, test, and manufacturing use cases. Work spans applied ML model development, deployment, and AI infrastructure to support organization-wide production workloads.
Experience Level
Senior. Typical experience expectations: PhD with 6+ years, MSEE with ~10+ years, or BSEE with ~12+ years (or equivalent experience).
Responsibilities
Primary responsibilities include developing applied AI solutions for chip test and design, and building the infrastructure to deploy and operate those solutions at scale.
- Design, develop, and deploy ML and generative-AI solutions for DFT and chip-design problems.
- Build and manage AI deployment cycles and infrastructure at an org-wide level.
- Act as liaison between on-prem infrastructure teams and software development teams; automate deployments and maintain CI/CD pipelines.
- Monitor system performance, perform performance tuning, and capacity planning for large-scale Gen AI workloads.
- Apply algorithm design and statistical analysis to interpret complex datasets from manufacturing and test.
- Develop and deploy DFT methodologies leveraging Gen AI; mentor junior engineers on test design trade-offs (cost, quality).
Requirements
Must-have technical skills and experience for immediate contribution.
- Proven experience in AI infrastructure management and applied machine learning for production systems.
- Strong knowledge of building agents and multi-agent ecosystems.
- Experience with SQL, ETL pipelines, and data modeling for large datasets.
- Hands-on experience with cloud platforms (AWS, Azure, GCP) and designing globally distributed systems for availability, latency, and throughput.
- Experience leading data modeling, performance tuning, and capacity planning for mission-critical Gen AI workloads.
- Proficiency in Python and C++.
- Strong written and verbal communication skills and ability to work on complex, uncommon problems.
Nice-to-have:
- Experience managing AI infrastructure for real-world, production systems.
- Prior experience applying AI to chip design or test problems.
- Demonstrated collaborative and influencing skills in dynamic engineering environments.
Education Requirements
Degree preferences listed by NVIDIA: BSEE (or equivalent experience) with ~12+ years, MSEE with ~10+ years, or PhD with ~6+ years. Fields referenced: Electrical Engineering (EE). The posting also accepts equivalent practical experience in lieu of a listed degree.
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.
