Senior Solutions Architect - Robotics AI & Simulation

NVIDIA Corporation; United States; Remote; USD 152,000 - 288,000; Full time

Benefits offered by this job

Equity

Benefits

Job summary

NVIDIA Corporation is hiring a hands-on Solutions Architect to design and scale Kubernetes-native environments for distributed Robotics workloads in the United States. You will collaborate with product and engineering teams to drive the adoption of Physical AI technologies across ecosystems.

The role emphasizes backend infrastructure, inference, and cloud-native apps, including guidance on deployment, scheduling, cost, and GPU utilization, with equity and benefits offered.

Qualifications

• BS in Computer Science, Computer Engineering, or related field or equivalent experience.
• 5+ years in Solution Architecture or Infrastructure Engineering for AI/ML systems on private/public clouds.
• Experience scaling Robotics workloads (training, inference, simulation, data processing).
• Hands-on design/deploy/operate Kubernetes platforms for distributed GPU/AI workloads.
• Expertise in networking (DNS, LB, TCP/IP), storage, orchestration (Airflow/Argo), and IaC/Observability.
• Excellent communication skills for diverse audiences.

Responsibilities

• Design and scale Kubernetes-native environments for distributed Robotics workloads.
• Develop scalable GPU-accelerated pipelines and data factories.
• Improve scheduling, storage access, and networking to optimize GPU utilization.
• Accelerate distributed inference using NVIDIA technologies (NIM, TensorRT-LLM, vLLM).
• Mentor customers and collaborate with product/engineering teams to adopt Physical AI.

Skills

Kubernetes

Cloud-native architectures

GPU workloads

Networking and storage

DevOps practices

Communication

Robotics AI knowledge

Education

BS in CS/CE or related field

Tools

Airflow

Argo

GitOps

IaC (Terraform/CloudFormation)

NVIDIA OSMO

NIM/TensorRT-LLM/vLLM

Job description

NVIDIA Corporation is hiring a hands-on Solutions Architect to design and scale Kubernetes-native environments for distributed Robotics workloads in the United States. You will collaborate with product and engineering teams to drive the adoption of Physical AI technologies across ecosystems.

The role emphasizes backend infrastructure, inference, and cloud-native apps, including guidance on deployment, scheduling, cost, and GPU utilization, with equity and benefits offered.