Software Engineering Intern, Robot Learning Platform – Shanghai | Visa + Salary Insights

📍 Location: Others

🏷 Type: Internship

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Job Overview

NVIDIA is hiring a Software Engineering Intern for its Robot Learning Platform team based in Shanghai. This role focuses on advancing next-generation robotics systems through simulation, reinforcement learning, and large-scale AI training infrastructure. The ideal candidate is a highly technical MS or PhD student in Computer Science, Robotics, or related fields with strong experience in Python, deep learning frameworks such as PyTorch, and robotics simulation tools. This internship places you directly within NVIDIA’s Isaac Lab ecosystem, contributing to cutting-edge research in autonomous systems, humanoid robotics, and sim-to-real deployment pipelines.

📅 Job Timeline & Status

This role is in an active hiring phase with strong competition due to NVIDIA’s global reputation in AI and robotics. Candidates should apply immediately as internship slots in advanced research teams tend to fill quickly. The position is likely in a mid-cycle recruitment phase with continuous rolling review, meaning strong profiles may be fast-tracked. Given the specialized robotics scope and MS/PhD requirement, early application significantly increases interview probability.

Role focus: Robotics AI systems, simulation-based learning, reinforcement learning research, MS/PhD-level engineering.

🌍 Work Eligibility & Location

This is a fully Onsite internship in Shanghai. International candidates may be considered, but visa sponsorship depends on profile strength and regulatory constraints. NVIDIA research internships typically support relocation for exceptional MS/PhD talent in robotics and AI systems.

💰 Salary Intelligence

This is a highly competitive internship with strong compensation relative to regional AI research roles. NVIDIA internships typically exceed industry averages, especially in robotics and deep learning teams. While exact figures are not public, the estimated range reflects top-tier AI lab internship benchmarks in China and global NVIDIA internship standards.

📊 Role Breakdown

This internship places you inside NVIDIA’s Isaac Lab ecosystem, focusing on building scalable robotics learning systems. You will work extensively with Python, PyTorch, and simulation frameworks like Isaac Sim and Mujoco. Around 35% of your time will involve developing reinforcement learning algorithms for robotic control, while 25% focuses on multi-agent and multi-task learning systems. Another 20% is dedicated to scaling cloud-based training pipelines, optimizing performance, and benchmarking large-scale models. The remaining 20% involves collaboration with research teams to integrate vision-language-action models and sim-to-real pipelines. You will also contribute to open-source Isaac Lab development, ensuring reproducibility and performance improvements across robotics workloads.

🧩 Required Skills & Fit

📈 Difficulty & Competitiveness

This is a highly selective research internship with strong emphasis on robotics AI depth. Candidates typically come from top-tier universities with prior RL or simulation experience. Expect rigorous screening due to NVIDIA’s elite robotics research focus.

🚀 Career Impact

This internship delivers exceptional long-term value, positioning candidates for elite roles in robotics, AI research, and autonomous systems engineering. Experience gained in Isaac Lab and NVIDIA’s robotics stack significantly strengthens profiles for both industry and academic research careers.

📋 Key Responsibilities

You will develop and optimize robot learning algorithms using Python and PyTorch, focusing on reinforcement learning and imitation learning pipelines. Responsibilities include building scalable simulation environments, improving Isaac Lab workflows, and contributing to multi-agent robotics systems. You will also work on performance optimization for cloud-based training infrastructure, ensuring efficient large-scale model execution. Collaboration with NVIDIA researchers is essential for integrating vision-language-action models and advancing sim-to-real transfer techniques. Additional tasks include benchmarking robotics models, profiling system performance, and contributing to open-source robotics frameworks used by the global research community.

🎯 Application Strategy

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📅 Application Signals

This role shows strong hiring momentum with active global interest due to NVIDIA’s leadership in robotics AI. With an estimated deadline window of a few weeks and high competition, applicants should prioritize immediate submission. Interview cycles for internship roles in research teams typically move within 2–4 weeks, with fast-tracking for strong ML or robotics profiles. Given the niche specialization, delays significantly reduce selection probability.

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✅ Job Source & Verification

This listing is sourced from NVIDIA’s official careers portal, ensuring high credibility and direct employer verification. The posting was last confirmed on May 31, 2026, based on platform timestamp (“Posted 6 days ago”). All details reflect the original job description and publicly available hiring information with no third-party modification.