NVIDIA

1 month ago

Full-Stack Solution Engineer - Sensorized Human

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI

Last checked: 17 hours agoStatus: Live

Job Summary

Lead hardware-software integration for the DexUMI wearable system, bridging human grip with robotic end-effectors through tactile sensing, ROS2, and AI-enabled perception. Own full-stack responsibilities from embedded firmware to cloud data pipelines, optimizing diffusion policies and imitation learning to advance dexterous manipulation in robotic systems.

Location: Shanghai, Beijing

Workplace: Onsite

Employment Type: Full time

Job Function: Solutions Engineering & Sales Engineering

Key Responsibilities

•Hardware-Software Co-Design: Maintain and iterate on the DexUMI wearable exoskeleton, bridging the kinematics between human hands and robot end-effectors.
•Sensor Fusion & Integration: Integrate high-fidelity tactile sensors and IMUs into wearable interfaces with low-latency data streaming.
•Vision & Perception Pipelines: Implement and optimize software adaptation layers to segment human operators from training data and robot embodiments.
•Data Engineering for AI: Build pipelines to collect, clean, and replay dexterous manipulation data for imitation learning and diffusion policies.
•Optimization: Solve bi-level optimization to parameterize exoskeleton designs maximizing wearability while preserving robot fingertip workspaces.

Key Requirements

•MS/PhD in Robotics, Machine Learning, Computer Science, Electrical Engineering, Mechanical Engineering or related field (or equivalent experience) with at least 1 year of research and engineering experience.
•Proficiency in C/C++ for embedded systems and ROS2, with hands-on experience in tactile sensing, force-feedback (haptics), and motor control.
•Experience with CAD (SolidWorks/Fusion360) and rapid prototyping, including 3D printing and PCB design.
•Expertise in Python and deep learning frameworks (PyTorch), with familiarity in computer vision models.
•Understanding of Imitation Learning or Reinforcement Learning is a strong plus and experience with Record3D or iPhone-based spatial tracking; Ubuntu/Linux environments; data serialization tools like Protobuf and MQTT.

Experience:1+ yearsRoboticsAiDeep learningComputer vision

Education:Master's

Skills:C/C++ROS2PythonPyTorchComputer VisionCADSolidWorksFusion3603D printingPCB designImitation LearningReinforcement LearningRecord3DIPhone spatial trackingUbuntuProtobufMQTT

Tech Stack:C/C++ROS2PythonPyTorchCADSolidWorksFusion3603D printingPCB designRecord3DIPhone spatial trackingUbuntuProtobufMQTTIMUsTactile sensing

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

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NVIDIA

1 month ago

Full-Stack Solution Engineer - Sensorized Human

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI

Last checked: 17 hours agoStatus: Live

Job Summary

Location: Shanghai, Beijing

Workplace: Onsite

Employment Type: Full time

Job Function: Solutions Engineering & Sales Engineering

Key Responsibilities

•Hardware-Software Co-Design: Maintain and iterate on the DexUMI wearable exoskeleton, bridging the kinematics between human hands and robot end-effectors.
•Sensor Fusion & Integration: Integrate high-fidelity tactile sensors and IMUs into wearable interfaces with low-latency data streaming.
•Vision & Perception Pipelines: Implement and optimize software adaptation layers to segment human operators from training data and robot embodiments.
•Data Engineering for AI: Build pipelines to collect, clean, and replay dexterous manipulation data for imitation learning and diffusion policies.
•Optimization: Solve bi-level optimization to parameterize exoskeleton designs maximizing wearability while preserving robot fingertip workspaces.

Key Requirements

•MS/PhD in Robotics, Machine Learning, Computer Science, Electrical Engineering, Mechanical Engineering or related field (or equivalent experience) with at least 1 year of research and engineering experience.
•Proficiency in C/C++ for embedded systems and ROS2, with hands-on experience in tactile sensing, force-feedback (haptics), and motor control.
•Experience with CAD (SolidWorks/Fusion360) and rapid prototyping, including 3D printing and PCB design.
•Expertise in Python and deep learning frameworks (PyTorch), with familiarity in computer vision models.
•Understanding of Imitation Learning or Reinforcement Learning is a strong plus and experience with Record3D or iPhone-based spatial tracking; Ubuntu/Linux environments; data serialization tools like Protobuf and MQTT.

Experience:1+ yearsRoboticsAiDeep learningComputer vision

Education:Master's

Skills:C/C++ROS2PythonPyTorchComputer VisionCADSolidWorksFusion3603D printingPCB designImitation LearningReinforcement LearningRecord3DIPhone spatial trackingUbuntuProtobufMQTT

Tech Stack:C/C++ROS2PythonPyTorchCADSolidWorksFusion3603D printingPCB designRecord3DIPhone spatial trackingUbuntuProtobufMQTTIMUsTactile sensing

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