NVIDIA

2 weeks ago

Senior Solutions Architect, Embedded Physical AI

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 26 minutes agoStatus: Live

Job Summary

Serve as a hands-on embedded systems and solutions expert for NVIDIA’s Physical AI ecosystem, bridging hardware bring-up, sensor integration, and deployment of next-generation robotics models. Work with customers and internal teams to turn prototypes into production-grade AI robotics stacks using NVIDIA platforms and edge AI tooling. Lead technical workshops and proof-of-concepts, translating requirements into practical architectures and feeding real-world field insights into product roadmaps.

Location: Santa Clara, California

Workplace: Hybrid

Employment Type: Full time

Job Function: Solutions Engineering & Sales Engineering

Seniority: Mid level

Key Responsibilities

•Act as the primary embedded systems expert for NVIDIA Physical AI partners using technologies such as Jetson, Holoscan, Isaac ROS/OS, and GR00T.
•Partner with customers to integrate production stacks, including real-time Linux, ROS 2, sensor pipelines, and edge AI models.
•Deploy, profile, and optimize robotics foundation models (VLAs, World Models) on embedded computers and advise on tradeoffs.
•Translate customer requirements into practical NVIDIA-based architectures and help internal teams incorporate field insights into product feedback.
•Lead technical discussions, presentations, and hands-on workshops; develop proof-of-concepts and reference implementations.

Pay and Benefits

Salary: USD 152,000 - 287,500 annually

Equity and Bonus:Equity

Key Requirements

•BS in Electrical Engineering, Computer Engineering, Computer Science, Robotics, Mechanical Engineering, or related field (or equivalent experience).
•5+ years of hands-on embedded systems experience, including developing on NVIDIA Jetson, performance tuning, and system-level debugging.
•Fluency in ROS 2 and experience deploying robotics autonomy stacks with sim-to-real validation workflows.
•Experience integrating sensor pipelines such as cameras, LiDAR, and IMU.
•Expertise deploying and optimizing AI models on edge hardware, including GPU profiling and SDKs like TensorRT.

Experience:5+ yearsRoboticsEmbedded systemsEdge AIAutonomous roboticsSim-to-real

Education:Bachelor's in Electrical Engineering, Computer Engineering, Computer Science, Robotics, Mechanical Engineering (or related)

Skills:CommunicationCollaborationTechnical translation

Tech Stack:JetsonHoloscanIsaac ROSIsaac OSGR00TROS 2LinuxTensorRTVLAsWorld ModelsVLMsCuVSLAMIsaac SimIsaac LabCosmosQuantizationCompressionDistillationHSBHoloscan Sensor Bridge

Company Brief

NVIDIA

Designs and manufactures GPUs, AI accelerators, and system-on-chip products for gaming, data centers, professional visualization, and automotive markets, enabling advanced graphics, AI, and high-performance computing solutions worldwide.

Industry: Electronics Manufacturing

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Santa Clara, United States

Founded: 1993

Glassdoor: 4.3

Website LinkedIn Glassdoor

Loading job details...

Preparing the role view and application actions.

NVIDIA

2 weeks ago

Senior Solutions Architect, Embedded Physical AI

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 26 minutes agoStatus: Live

Job Summary

Location: Santa Clara, California

Workplace: Hybrid

Employment Type: Full time

Job Function: Solutions Engineering & Sales Engineering

Seniority: Mid level

Key Responsibilities

•Act as the primary embedded systems expert for NVIDIA Physical AI partners using technologies such as Jetson, Holoscan, Isaac ROS/OS, and GR00T.
•Partner with customers to integrate production stacks, including real-time Linux, ROS 2, sensor pipelines, and edge AI models.
•Deploy, profile, and optimize robotics foundation models (VLAs, World Models) on embedded computers and advise on tradeoffs.
•Translate customer requirements into practical NVIDIA-based architectures and help internal teams incorporate field insights into product feedback.
•Lead technical discussions, presentations, and hands-on workshops; develop proof-of-concepts and reference implementations.

Pay and Benefits

Salary: USD 152,000 - 287,500 annually

Equity and Bonus:Equity

Key Requirements

•BS in Electrical Engineering, Computer Engineering, Computer Science, Robotics, Mechanical Engineering, or related field (or equivalent experience).
•5+ years of hands-on embedded systems experience, including developing on NVIDIA Jetson, performance tuning, and system-level debugging.
•Fluency in ROS 2 and experience deploying robotics autonomy stacks with sim-to-real validation workflows.
•Experience integrating sensor pipelines such as cameras, LiDAR, and IMU.
•Expertise deploying and optimizing AI models on edge hardware, including GPU profiling and SDKs like TensorRT.

Experience:5+ yearsRoboticsEmbedded systemsEdge AIAutonomous roboticsSim-to-real

Education:Bachelor's in Electrical Engineering, Computer Engineering, Computer Science, Robotics, Mechanical Engineering (or related)

Skills:CommunicationCollaborationTechnical translation

Tech Stack:JetsonHoloscanIsaac ROSIsaac OSGR00TROS 2LinuxTensorRTVLAsWorld ModelsVLMsCuVSLAMIsaac SimIsaac LabCosmosQuantizationCompressionDistillationHSBHoloscan Sensor Bridge

Company Brief

NVIDIA

Industry: Electronics Manufacturing

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Santa Clara, United States

Founded: 1993

Glassdoor: 4.3

Website LinkedIn Glassdoor