Senior Research Scientist, Design Automation Research at NVIDIA

Santa Clara, California, United States

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Not SpecifiedCompensation

Senior (5 to 8 years), Expert & Leadership (9+ years)Experience Level

Full TimeJob Type

UnknownVisa

Technology, SemiconductorIndustries

Requirements

PhD in Computer Science, Electrical/Computer Engineering, or related field (or equivalent experience), with 3+ years of post-PhD research experience and a strong record of impactful publications in top EDA and AI/ML venues; proven ability to set research direction and translate ideas into tools or products
Deep knowledge in EDA/VLSI (e.g., synthesis, physical design, verification, timing, reliability, or CAD algorithms) combined with 5+ years applying machine learning/deep learning (supervised, unsupervised, RL) and GPU/accelerator-based computing to large-scale problems
5+ years of experience in software development with proficiency in at least two of Python, PyTorch, C++, or CUDA; strong expertise in high-performance computing, parallelism, optimization, and large-scale software engineering
Experience in leading research projects or teams, with a track record of mentoring junior scientists, driving cross-functional initiatives with circuits/VLSI/architecture groups, and fostering collaborations with academia or industry
Excellent written and verbal communication skills, with demonstrated experience presenting at top conferences; track record of releasing high-impact open-source tools, datasets, or frameworks; ability to influence both technical and non-technical audiences

Responsibilities

Define and conduct original research across EDA algorithms, VLSI design methodology, and advanced machine learning techniques
Innovate in EDA software and algorithms, with applications spanning supervised, unsupervised, and reinforcement learning, as well as GPU-accelerated optimization methods
Apply deep learning and GPU computing to improve ASIC and VLSI design tool flows
Collaborate cross-functionally with circuit design, VLSI, and architecture teams, ensuring research translates into real-world product impact
Engage with the global research community by publishing in premier conferences, presenting at leading venues, and driving thought leadership
Foster collaboration with external researchers and diverse internal product teams to amplify research outcomes

Skills

EDA

VLSI

Machine Learning

Deep Learning

Reinforcement Learning

GPU Computing

ASIC Design

Synthesis

Physical Design

Verification

Timing Analysis

CAD Algorithms

NVIDIA

Designs GPUs and AI computing solutions

About NVIDIA

NVIDIA designs and manufactures graphics processing units (GPUs) and system on a chip units (SoCs) for various markets, including gaming, professional visualization, data centers, and automotive. Their products include GPUs tailored for gaming and professional use, as well as platforms for artificial intelligence (AI) and high-performance computing (HPC) that cater to developers, data scientists, and IT administrators. NVIDIA generates revenue through the sale of hardware, software solutions, and cloud-based services, such as NVIDIA CloudXR and NGC, which enhance experiences in AI, machine learning, and computer vision. What sets NVIDIA apart from competitors is its strong focus on research and development, allowing it to maintain a leadership position in a competitive market. The company's goal is to drive innovation and provide advanced solutions that meet the needs of a diverse clientele, including gamers, researchers, and enterprises.

Santa Clara, CaliforniaHeadquarters

1993Year Founded

$19.5MTotal Funding

IPOCompany Stage

Automotive & Transportation, Enterprise Software, AI & Machine Learning, GamingIndustries

10,001+Employees

Benefits

Company Equity

401(k) Company Match

Risks

Increased competition from AI startups like xAI could challenge NVIDIA's market position.

Serve Robotics' expansion may divert resources from NVIDIA's core GPU and AI businesses.

Integration of VinBrain may pose challenges and distract from NVIDIA's primary operations.

Differentiation

NVIDIA leads in AI and HPC solutions with cutting-edge GPU technology.

The company excels in diverse markets, including gaming, data centers, and autonomous vehicles.

NVIDIA's cloud services, like CloudXR, offer scalable solutions for AI and machine learning.

Upsides

Acquisition of VinBrain enhances NVIDIA's AI capabilities in the healthcare sector.

Investment in Nebius Group boosts NVIDIA's AI infrastructure and cloud platform offerings.

Serve Robotics' expansion, backed by NVIDIA, highlights growth in autonomous delivery services.

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