
Pioneering accelerated computing and AI
Senior Solutions Architect, Autonomous Driving - GenAI at NVIDIA
About the role
NVIDIA is building the world’s leading AI company, and we are looking for an expert AV and GenAI Solutions Architect to help assist customers with adoption of NVIDIA's full-stack technologies as well as building and deploying solutions around Generative AI and Physical AI and other related GPU-accelerated technologies in which intelligent agents can learn, reason, and interact the world. As part of the Automotive Solutions Architecture team, we work with some of the most innovative accelerated computing platforms focused on the development and test of autonomous vehicles, in-vehicle AI assistance, and ride sharing algorithms among other things. A Solutions Architect is the first line of technical expertise between NVIDIA and customers so you will engage directly with developers, researchers, and visionary scientists at some of the most strategic customers as well as work directly with business and engineering teams on product strategy as it pertains to these customers. Join us in this exciting endeavor!
What you'll be doing:
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Engage with customers to help them scope and develop solutions for building AV perception and planning models and pipelines, simulations, synthetic data generation, and software in the loop testing, AI enhanced manipulation and navigation workflows using NVIDIA's Physical AI platforms and CUDA-X libraries.
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Provide hands-on technical mentorship to partners and customers on Nvidia GenAI stack. Guide customers to develope and deploy Agentic AI workflows on our platforms, quantifying the benefits of our accelerated computing software and hardware.
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Partner with Sales, Engineering, Product and other Solution Architect teams to drive NVIDIA full stack adoption. Develop a deep understanding of customer workflows and requirements, lead proof-of-concepts evaluations and provide internal feedback to drive continuous product improvements.
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Build collateral (notebooks, github repos, demos, etc.) applied to workflows such as AV and GenAI data curation, model training and validations, LLMs, VFMs, video encoding/decoding, etc.
What we need to see:
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Master's or Ph.D. in Computer Science, Artificial Intelligence, or equivalent experience.
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8+ years of hands-on experience in a technical AI role, with a strong emphasis on AV End-to-End models and GenAI model development.
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Experience writing production codes in Python, or C++ and proficiency with Linux.
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Hands-on experience with DevOps tools such as GitLab, Docker, and Kubernetes.
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Strong understanding of AV systems (Sensors, dynamics, perception, prediction, planning, control).
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Experience with DL and RL algorithms and frameworks such as Py Torch.
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Enjoy working with multiple levels and teams across organizations (engineering/research, product, sales and marketing teams).
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Effective verbal/written communication, and technical presentation skills.
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Self-starter with a vision for growth, real passion for continuous learning and sharing findings across the team.
Ways to stand out from the crowd:
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Experience with AV sensors, data curation pipelines, world models, simulations workflows and tools e.g., Carla.
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Experience with Agentic AI frameworks, tools, and protocols like Lang Chain, Lang Graph, MCP or equivalent experience.
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Understand computational characteristics of Multimodal LLMs, VLMs, DiT, etc.
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Experience in deploying LLM models at scale on mainstream cloud providers (e.g., AWS, Azure, GCP).
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Proven track record to profile and optimize inference latency and throughput, memory and I/O utilization.
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until May 9, 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.
Required skills
Solutions architecture
Autonomous driving
Generative AI
Simulation
Synthetic data
Customer enablement
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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
Junior/L3
Mid/L4
Senior/L5
Junior/L3 · Analyst
7 reports
$170,275
total per year
Base
$130,981
Stock
-
Bonus
-
$155,480
$234,166
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
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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.
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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.
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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.
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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.
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