Senior Solutions Architect, Autonomous Vehicles and Robotics 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

Autonomous Vehicles, RoboticsIndustries

Requirements

Master’s degree or equivalent experience in Computer Science, Electrical Engineering, Robotics, or a related technical field
5+ years of hands-on, proven experience in Autonomous Vehicles, Robotics, or Physical AI
Proficiency in Python or C++ and experience with Linux
Experience with DevOps tools such as GitLab, Docker, and Kubernetes
Strong understanding of AV and Robotics systems (Sensors, dynamics, perception, prediction, planning, control)
Experience with Deep Learning (DL) and Reinforcement Learning (RL) algorithms, standards such as OpenAI Gym, and frameworks like PyTorch
Ability to communicate technical ideas and code clearly through blog posts, GitHub, and presentations

Responsibilities

Engage with customers to help them scope and develop solutions for training AV and Robotics perception and policy models, simulations, synthetic data generation, software in the loop testing, and AI-enhanced manipulation and navigation workflows using NVIDIA’s Isaac Sim, Omniverse, Cosmos, and other relevant platforms
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-concept evaluations, and provide internal feedback to drive continuous product improvements
Share domain expertise with the NVIDIA solutions architect community and stay updated on advancements in AV, Robotics, Physical AI, and Gen AI
Provide technical mentorship to partners and customers
Develop and demonstrate solutions based on NVIDIA’s groundbreaking software and hardware technologies to customers
Perform in-depth analysis and optimization of state-of-the-art AI models to ensure the best performance on current- and next-generation GPU architectures
Build collateral (notebooks, GitHub repos, demos, etc.) applied to workflows such as AV and Robotics model training and validations, LLMs, VFMs, video encoding/decoding, etc

Skills

Python

C++

Linux

GitLab

Docker

Kubernetes

PyTorch

Deep Learning

Reinforcement Learning

OpenAI Gym

Isaac Sim

Omniverse

Cosmos

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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