Senior Applied AI and AI Infrastructure Engineer - Chip Design and DFX
at Nvidia
USD 200,000-379,500 per year
Used Tools & Technologies
GenAIRequired Skills & Competences
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Software Development @ 4
Python @ 7
SQL @ 4
GCP @ 4
ETL @ 4
Distributed Systems @ 4
Machine Learning @ 7
AWS @ 4
Azure @ 4
Communication @ 4
Generative AI @ 4
AI @ 4
Data Modeling @ 4
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
NVIDIA is a learning machine that constantly evolves by adapting to new opportunities. Design-for-X Engineering at NVIDIA works on innovations applying AI to Chip Design and Predictions for manufacturing testing on complex semiconductor chips.
Responsibilities
- Work as a senior member on Applied AI projects requiring ML and Generative AI expertise.
- Build and manage deployment cycles as part of AI infrastructure requirements at an org-wide level.
- Act as liaison between on-prem infrastructure teams and software development teams while monitoring performance, automating deployments, and maintaining code pipelines.
- Solve hard problems in the Design For Test (DFT) space using algorithm design, statistical analysis of complex datasets, and Applied AI methods.
- Develop and deploy DFT methodologies for next-generation products using Gen AI solutions.
- Mentor junior engineers on test designs, trade-offs, cost, and quality.
Requirements
- BSEE (or equivalent experience) with 12+ years, MSEE with 10+ years, or PhD with 6+ years of experience in AI infrastructure management, Applied Machine Learning and Generative AI.
- Excellent knowledge in building agents and multi-agent ecosystems.
- Experience with SQL, ETL, and data modeling.
- Hands-on experience with cloud platforms (AWS, Azure, GCP).
- Experience architecting and optimizing multi-region, globally distributed systems for availability, latency, and throughput.
- Experience leading data modeling, performance tuning, and capacity planning for large-scale mission-critical Gen AI workloads.
- Strong programming skills in Python and C++.
- Outstanding written and oral communication skills and curiosity for rare challenges.
Ways to stand out
- Prior experience in AI infrastructure management for real-world systems.
- Experience applying AI to chip design problem-solving.
- Strong collaborative and interpersonal skills, with a proven ability to guide and influence in a dynamic environment.
Compensation and benefits
- Base salary ranges provided by location and level:
- Level 5: 200,000 USD - 322,000 USD
- Level 6: 248,000 USD - 379,500 USD
- Eligibility for equity and additional benefits (link to NVIDIA benefits referenced in original posting).
Additional information
- Applications accepted at least until June 6, 2026.
- This posting is for an existing vacancy.
- NVIDIA uses AI tools in its recruiting processes.
- NVIDIA is an equal opportunity employer committed to fostering an inclusive work environment.