Robotics AI Solutions Architect Scalable GPU Cloud

NVIDIA; California (MO); On-site; USD 152,000 - 288,000; Full time

Benefits offered by this job

Equity

Benefits

Job summary

NVIDIA is seeking a hands-on Solutions Architect to design and scale Kubernetes-native environments for distributed Robotics workloads, accelerating Physical AI pipelines and data factories. You will partner with product, engineering, and business teams to drive adoption of NVIDIA’s Physical AI technologies at scale.

You will work on cloud-native architectures, optimize scheduling, cost, and GPU utilization, and mentor customers through production deployment.

Qualifications

• BS in Computer Science, Computer Engineering, or related field, or equivalent experience.
• 5+ Years of experience in Solution Architecture or Infrastructure Engineering, advancing AI/ML systems from proof of concept to production on private/public cloud environments.
• Experience scaling Robotics workloads in multimodal model training, inference, robot learning and simulation, large scale data processing and generation.
• Strong hands-on experience designing, deploying, and operating Kubernetes-based platforms for distributed GPU and AI workloads.
• Expertise in networking (DNS, LB, TCP/IP, firewalls), storage technology, workflow orchestration softwares (Airflow, Argo, etc), modern DevOps practices (GitOps, IaC, Observability), and orchestrating efficient GPU workloads
• Excellent communication skills to convey technical concepts to diverse audiences.

Responsibilities

• Help partners build scalable, observable, GPU-accelerated Physical AI pipelines through agentic workflows, cloud-native technologies, and NVIDIA frameworks such as OSMO.
• Support development of Physical AI data factories for data ingestion, preprocessing, annotation, filtering, synthetic data generation, training, simulation, and evaluation.
• Develop a deep understanding of robotics workload scaling and translate customer requirements into optimized cloud-native architectures, improving scheduling, cost, storage access, networking, and GPU utilization across hybrid infrastructure.
• Accelerate distributed inference using NVIDIA technologies such as NIM, TensorRT-LLM, vLLM, and SGLang.
• Collaborate with business, engineering, and product teams while providing technical guidance and mentorship to customers implementing Physical AI at scale.

Skills

Solution Architecture

AI/ML systems deployment

Cloud-native design

Networking & Observability

Communication

Education

BS in Computer Science or Computer Engineering

Tools

Kubernetes

Airflow

Argo

GitOps

Infrastructure as Code

REST/gRPC APIs

Job description

NVIDIA is seeking a hands-on Solutions Architect to design and scale Kubernetes-native environments for distributed Robotics workloads, accelerating Physical AI pipelines and data factories. You will partner with product, engineering, and business teams to drive adoption of NVIDIA’s Physical AI technologies at scale.

You will work on cloud-native architectures, optimize scheduling, cost, and GPU utilization, and mentor customers through production deployment.