Applied Machine Learning Engineer - VLSI Design

Reposted 2 Days Ago
Santa Clara, CA
In-Office
136K-265K Annually
Senior level
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
The Role
Collaborate on hardware design projects, translating requirements into data science solutions, optimizing models, and integrating with machine learning tools.
Summary Generated by Built In

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people.

Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.

What you'll be doing:

  • Work within a multi-functional team on various projects involving Pre-silicon and Post Silicon hardware design and related data, Circuit 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.

  • Test 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.

What we need to see:

  • MS/PhD in Electrical/Computer Engineering, Computer Science, Applied Mathematics (or equivalent experience)

  • 5+ years experience in circuit design, VLSI, ASIC, EDA, Silicon analysis is required

  • Prior experience in Applied Math/ML/Software programming with proven ability in writing code in Python, C++

  • Experience with ML/DL algorithms with frameworks such as TensorFlow, PyTorch, Spark is a definite plus

Ways to stand out from the crowd:

  • Enjoy working with multiple levels and teams across organizations (engineering/research, product, sales and marketing teams)

  • Effective verbal/written communication, and technical presentation skills

  • Self-starter with passion for growth, real enthusiasm for continuous learning and sharing findings across the team

NVIDIA is a pioneer in bringing groundbreaking technology to new markets. We have some of the most forward-thinking and hardworking people in the world working with us. If you're creative and autonomous, we want to hear from you!

#LI-Hybrid

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 136,000 USD - 218,500 USD for Level 3, and 168,000 USD - 264,500 USD for Level 4.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until January 27, 2026.

This posting is for an existing vacancy. 

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

Top Skills

C++
Python
PyTorch
Spark
TensorFlow
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The Company
HQ: Santa Clara, CA
21,960 Employees
Year Founded: 1993

What We Do

NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”

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