Lead development of Agentic AI capabilities and LLM applications for multiple mission management applications. Mentor teams to implement ML algorithms addressing customer challenges.
About the role
- Applied Machine Learning Engineer designing and optimizing circuits in a multi-functional team at NVIDIA. Working on various silicon-related projects and utilizing machine learning techniques for circuit design and analysis.
Responsibilities
- Work within a multi-functional team on various projects involving Pre-silicon and Post Silicon custom circuit design and related data.
- Circuit/Layout Optimization and Spice correlation.
- Work on projects with applications ranging from analysis of silicon data, manufacturing process variation analysis, VLSI circuit design and timing etc.
- Responsible for translating the requirements into a data science problem, architect and build solutions.
- In charge for testing and release of models that integrate with existing machine learning and visualization tools within the organization.
- Responsible for analyzing the datasets, raise and validate hypotheses, extract relevant features and build models on top of them.
- Optimize the models and algorithms until they reach the desired QOR.
Requirements
- MS or PhD in Electrical/Computer Engineering (or equivalent experience).
- Experience with VLSI, Circuit Design, CMOS Device Physics, Timing, ASIC, EDA is a strict requirement for this role.
- Shown ability in writing code in Python and C++.
- Experience in Applied Math/ML/Software programming.
Benefits
- equity
- benefits
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