Senior Solutions Architect, Autonomous Driving - GenAI 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

Automotive, Artificial IntelligenceIndustries

Requirements

Master's or Ph.D. in Computer Science, Artificial Intelligence, or equivalent experience
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
Experience writing production codes in Python, or C++ and proficiency with Linux
Hands-on experience with DevOps tools such as GitLab, Docker, and Kubernetes
Strong understanding of AV systems (Sensors, dynamics, perception, prediction, planning, control)
Experience with DL and RL algorithms and frameworks such as PyTorch
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 a vision for growth, real passion for continuous learning and sharing findings across the team

Responsibilities

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
Provide hands-on technical mentorship to partners and customers on Nvidia GenAI stack. Guide customers to develop and deploy Agentic AI workflows on our platforms, quantifying the benefits of our accelerated computing software and hardware
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
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

Skills

Generative AI

Autonomous Driving

CUDA-X

Physical AI

Agentic AI

GPU

AV Perception

Planning Models

Simulations

Synthetic Data Generation

Software in the Loop Testing

CUDA

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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