Senior Solutions Architect, Physical AI Cloud

🕒 August 10

🏄 California – Remote

🏄 California – Remote

💵 $152k - $287.5k / year

⏰ Full Time

🟠 Senior

💻 Solutions Engineer

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👻 Ghost score 18%

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NVIDIA

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1993

🏥 Healthcare

🏭 Manufacturing

🤖 Artificial Intelligence

Healthcare • Manufacturing • Artificial Intelligence

NVIDIA is a leading technology company specializing in accelerated computing and artificial intelligence. NVIDIA pioneers advancements in graphical processing units (GPUs), cloud computing, data centers, and virtual reality, with a focus on gaming, automotive, healthcare, and robotics industries. The company's innovations, such as NVIDIA Omniverse, transform traditional digital processes by enabling high-fidelity simulations and rendering tasks. Their applications span various industries, from autonomous vehicles using NVIDIA DRIVE to healthcare solutions with NVIDIA Clara, and AI-driven analytics and workflows.

📋 Description

• 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. • Improve 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. • Provide technical guidance and mentorship to customers implementing Physical AI at scale.

🎯 Requirements

• BS in Computer Science, Computer Engineering, or a related field, or equivalent experience. • 5+ years of experience in Solution Architecture or Infrastructure Engineering. • Experience 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, or 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, including DNS, load balancing, TCP/IP, and firewalls. • Expertise in storage technology. • Expertise with workflow orchestration software such as Airflow and Argo. • Expertise in modern DevOps practices including GitOps, IaC, and observability. • Experience orchestrating efficient GPU workloads. • Excellent communication skills to convey technical concepts to diverse audiences. • Preferred: hands-on experience with robotics frameworks such as ROS2 and NVIDIA platforms such as Isaac Lab, Isaac Sim, GR00T, or Cosmos. • Preferred: exposure to large-scale Robotics data curation, annotation, and filtering pipelines, including AI models for data labeling. • Preferred: experience deploying NVIDIA inference technologies such as Dynamo, NIM, Triton, and vLLM using quantization. • Preferred: proficiency using and developing agentic workflows. • Preferred: broad technical expertise across networking, compute, and storage systems such as S3, NFS, and Lustre, with hands-on experience building and debugging REST and gRPC APIs.

🏖️ Benefits

• Equity • Benefits

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