
Pioneering accelerated computing and AI
Applied AI Engineer - Silicon Co-Design Group at NVIDIA
About the role
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.
NVIDIA's Silicon Co-Design Group is seeking an Applied AI Engineer to innovate, develop, and integrate innovative AI solutions into the design and automation infrastructure that powers our chips. Every CPU, GPU, and Tegra SoC NVIDIA has shipped in the past four years passed through our toolchain on its way to production — over 200 product SKUs were optimized during the Blackwell generation alone. Now we're rebuilding that toolchain around AI, and we're looking for the engineer to lead that charge. In this role, you will architect and implement solutions that enhance the efficiency, scalability, and intelligence of our workflows, driving initiatives from concept to deployment. If you combine deep technical expertise with a hands-on approach and an aim to push the boundaries of what's possible, this is your opportunity. At NVIDIA, we strive for perfection, encourage innovation, and provide opportunities to explore new ways to succeed!
What you'll be doing:
-
Designing and implementing AI/LLM-powered systems to improve post-silicon validation, automation, and workflow efficiency within semiconductor validation environments.
-
Collaborating with multi-functional engineering teams to find opportunities for AI integration and performance optimization.
-
Evaluating emerging frameworks, architectures, and tools to improve efficiencies powered by artificial intelligence across the organization.
-
Establish and maintain data-driven indicators to quantify AI impact, identify performance gaps, and drive continuous improvement across systems.
What we need to see:
-
BS, MS, or PhD or equivalent experience in CS, EE, CE, or a related field, with 5+ years of hands-on experience building and deploying ML/AI systems or data-intensive backend services.
-
2+ years of direct Applied AI experience independently owning an AI agent, LLM-powered workflow, or intelligent automation system end-to-end — from prototype through production deployment.
-
Strong Python skills and proficiency in at least one static language such as C, C++, C#, Java, or Scala.
-
Demonstrated experience with deep learning frameworks like Py Torch or Tensor Flow, and hands-on experience with agentic and orchestration tools including Ne Mo Agent Toolkit, Lang Chain, Semantic Kernel, Auto Gen, CrewAI, or n8n.
-
Proven track record with deploying, monitoring, and debugging scalable AI/ML models.
-
Ability to balance multiple simultaneous projects.
-
Excellent problem-solving, communication, and collaboration skills.
Ways to stand out from the crowd:
-
Familiarity with modern AI technologies and methodologies for crafting and launching LLMs.
-
Experience with building and deploying orchestration agents managing hundreds to thousands of tools.
-
Ability to translate innovative AI research into practical, high-impact production tools.
-
Experience working within a silicon development environment, with exposure to chip and system characterization methodologies.
Widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family www.nvidiabenefits.com
Required skills
applied AI
machine learning
software engineering
automation
system design
Total Views
0
Total Apply Clicks
0
Total Mock Apply
0
Total Bookmarks
0
More open roles at NVIDIA

Senior Software Engineer - GPU Networking
NVIDIA · US, CA, Santa Clara

Senior System Software Test Engineer, Networking
NVIDIA · US, CA, Santa Clara

Manager, Networking Software Test
NVIDIA · US, CA, Santa Clara

Senior Firmware Engineer, Networking
NVIDIA · US, CA, Santa Clara

Senior Software K8S Engineer
NVIDIA · 5 Locations
Similar jobs

Principal Speech Recognition Researcher (Onsite)
Collins Aerospace (RTX) · US-MD-COLUMBIA-720 ~ 9861 Broken Land Pkwy ~ BBN COLUMBIA, Ste 400

Senior Speech Recognition Researcher (Onsite)
Collins Aerospace (RTX) · US-MD-COLUMBIA-720 ~ 9861 Broken Land Pkwy ~ BBN COLUMBIA, Ste 400

Generative AI Software Developer/Engineer – Aerospace Technologies (Onsite)
RTX (Raytheon) · US-IA-CEDAR RAPIDS-124 ~ 400 Collins Rd NE ~ BLDG 124

AI Engineer
Rockwell Automation · Singapore, Singapore

AI Engineer
Rockwell Automation · Milwaukee; Mayfield Heights
About NVIDIA

NVIDIA
PublicA computing platform company operating at the intersection of graphics, HPC, and AI.
10,001+
Employees
Santa Clara
Headquarters
$4.57T
Valuation
Reviews
10 reviews
4.4
10 reviews
Work-life balance
2.8
Compensation
4.5
Culture
4.2
Career
4.3
Management
3.8
78%
Recommend to a friend
Pros
Cutting-edge technology and innovation
Excellent compensation and benefits
Great team culture and collaboration
Cons
High pressure and expectations
Poor work-life balance and long hours
Fast-paced environment leading to burnout
Salary Ranges
79 data points
L3
L4
L5
L3 · Data Scientist IC2
0 reports
$177,542
total per year
Base
-
Stock
-
Bonus
-
$150,910
$204,174
Interview experience
5 interviews
Difficulty
3.0
/ 5
Interview process
1
Application Review
2
Recruiter Screen
3
Technical Phone Screen
4
Onsite/Virtual Interviews
5
Team Matching
6
Offer
Common questions
Coding/Algorithm
System Design
Behavioral/STAR
Technical Knowledge
Past Experience
Latest updates
Negotiating NVIDIA's Offer
Base, stock, and sign-on negotiable. Recruiters invested in closing candidates. CEO reviews all 42K employee salaries monthly. Stock growth has made many employees millionaires.
reddit/blind
·
NVIDIA Company Reviews
WLB rated 3.9/5 (lowest category). 64% satisfied with WLB but 53% feel burnt out. Compensation rated 4.4-4.5/5. Experience highly team-dependent.
reddit/blind
·
NVIDIA Interview Discussions
Technical bar is high with 4-6 rounds. Process takes 4-8 weeks. Expect C++ questions, LeetCode medium, and system design. Difficulty rated 3.16/5.
reddit/blind
·
NVIDIA Culture Discussions
Team-dependent experience; sink-or-swim culture that rewards high performers but can be overwhelming. No politics, flat structure, but demanding workload with some teams requiring evening/weekend work.
reddit/blind
·