Senior Applied AI and AI Infrastructure Engineer - Chip Design and Dfx

NVIDIA NVIDIA · Semiconductors · Santa Clara, CA

Senior Engineer focused on Applied AI and AI Infrastructure for Chip Design and DFX at NVIDIA. The role involves building and managing deployment cycles for ML & Gen AI projects, establishing robust AI infrastructure, and applying AI methods to solve complex problems in Design For Test. Requires expertise in agents, multi-agentic ecosystems, SQL, ETL, data modeling, cloud platforms, and strong programming skills in Python/C++.

What you'd actually do

  1. As a senior member in our team, you will work on Applied AI projects that requires ML & Gen AI expertise.
  2. You will work on building and managing deployment cycles as part of the AI Infrastructure requirements at an org-wide level.
  3. For setting up a robust AI infrastructure, you will be the liaison between on-prem infrastructure teams and SW dev teams, while monitoring performance, automating deployments and maintaining code pipelines.
  4. You will work on hard-to-solve problems in the Design For Test space which will involve application of algorithm design, using statistical tools to analyze and interpret complex datasets and explorations using Applied AI methods.
  5. In addition, you will help develop and deploy DFT methodologies for our next generation products using Gen AI solutions.

Skills

Required

  • AI Infrastructure management
  • Applied Machine Learning
  • Gen AI
  • building agents and multi-agentic ecosystems
  • SQL
  • ETL
  • data modeling
  • cloud platforms (AWS, Azure, GCP)
  • Architect and optimize multi-region, globally distributed systems
  • Lead data modeling, performance tuning, and capacity planning for large-scale mission-critical Gen AI workloads
  • Python
  • C++

Nice to have

  • Experience in Ai infrastructure management for real-world systems
  • Experience in application of AI for Chip Design problem-solving
  • Good understanding of technology
  • Strong collaborative and interpersonal skills
  • proven ability to effectively guide and influence within a dynamic environment

What the JD emphasized

  • Excellent knowledge in building agents and multi-agentic ecosystems
  • Strong programming skills in Python, C++ expected

Other signals

  • Applied AI projects
  • AI Infrastructure requirements
  • deployment cycles
  • Gen AI solutions
  • agents and multi-agentic ecosystems