This position is no longer accepting applications
Closed on August 12, 2026.
This role is filled — get an email when new Data Analysis roles open on DataJobs.io:
Senior Applied Machine Learning Engineer - VLSI Design
Senior
Agent Based Design
Analytics
Artificial Intelligence
Circuit Design
Data Analysis
Data Analytics
Design Automation
Engineer
Engineering
Generative AI
Hardware Engineering
Hardware Software Co Design
Machine Learning Engineer
Programming Languages
View similar jobs
Get alerted when similar jobs are posted — set up a New Data Analysis jobs on DataJobs.io alert.
See other roles at NVIDIA.
Job Description
Senior Applied Machine Learning Engineer focusing on VLSI/EDA design automation at NVIDIA, building data science and AI/agentic systems to accelerate pre- and post-silicon hardware design and circuit optimization, with integration into existing tools.
Responsibilities
- Collaborate within a multi-functional team on projects involving pre-silicon and post-silicon hardware design data, circuit optimization, SPICE correlation, and AI systems for EDA/design automation.
- Contribute to applications spanning silicon data analysis, manufacturing process variation analysis, VLSI circuit design, timing, and agent-driven design exploration and agent flow optimization.
- Translate requirements into data science, AI/ML, and agentic system problems; architect and build robust solutions.
- Test and release models and AI systems that integrate with existing machine learning, design automation, and visualization tools within the organization.
- Analyze datasets, formulate and validate hypotheses, extract relevant features, and develop models and self-improving workflows on top of them.
- Optimize models, algorithms, and autonomous optimization systems until achieving the desired quality of results (QOR).
Requirements
- MS or PhD in Electrical/Computer Engineering, Computer Science, Applied Mathematics, or equivalent experience.
- 4+ years of experience in circuit design, VLSI, ASIC, EDA, silicon analysis, or custom circuit design.
- Experience in Applied Math/ML/Software programming with proven ability in Python and C++.
- Experience with deep learning algorithms and AI agent frameworks; familiarity with PyTorch, LangChain, or LangGraph is a definite plus.
Technologies
- Python
- C++
- PyTorch
- LangChain
- LangGraph
Benefits
- Equity
- Benefits
Ways to Stand Out From the Crowd
- Experience building AI systems for EDA, design automation, or circuit design workflows.
- Research or project experience in AI-driven EDA, circuit optimization, design-space exploration, or autonomous design systems.
- Experience building agentic systems, autonomous optimization loops, self-improving AI systems, or production-scale AI/ML platforms.
- Effective verbal and written communication and technical presentation skills.
- Self-starter with a passion for growth, continuous learning, and sharing findings across the team.