Hybrid Applied Machine Learning Engineer, Circuit Design

at NVIDIA

• Job title: Applied Machine Learning Engineer, Circuit Design
• Job type: Full Time
• Experience level: Mid level, Senior
• Salary: $116,000 - $218,500 per year
• Degree requirement: Postgraduate Degree
• Tech skills: Python
• Location requirements: Hybrid, Santa Clara, United States

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