Senior Solutions Architect, Physical AI Cloud at NVIDIA
About the role
We're building a group of innovators to assist enterprises in deploying and accelerating NVIDIA’s three computer workloads for Physical AI. These include robotics simulation, synthetic data generation, multi-step model training, and inference, all on a large scale! We are seeking a hands-on Solutions Architect with deep expertise in backend infrastructure, inference and cloud-native applications to design and scale Kubernetes-native environments for distributed Robotics workloads. This role off…
Interview process at NVIDIA
Deep technical, domain-heavy. Coding rounds are LeetCode medium-to-hard; expect CUDA/GPU/parallelism questions for infra roles and low-level systems questions for driver/compiler roles.
- Recruiter screen (30 min)
- Hiring manager technical (45-60 min, 1 coding + domain probing)
- Full loop: 4-5 rounds - 2 coding, 1 domain deep-dive (CUDA/parallel/ML/systems depending on role), 1 design, 1 behavioral
- Cross-team panel
- Offer
Platforms used: unknown — MiPrep tested compatible with major platforms
How to prepare
MiPrep helps you rehearse the specific cadence and question types NVIDIA interviewers score on. Upload your resume and this job description; MiPrep generates a rehearsed answer set in your voice from your own projects.