10 days ago
Base Salary
$152k - $288k/yr
Responsibilities
- Help partners build scalable, observable, GPU-accelerated Physical AI pipelines using agentic workflows, cloud-native technologies, and NVIDIA frameworks such as OSMO.
- Support Physical AI data factories covering ingestion, preprocessing, annotation, filtering, synthetic data generation, training, simulation, and evaluation.
- Translate customer requirements into optimized cloud-native architectures for robotics workload scaling across hybrid infrastructure.
- Improve scheduling, cost, storage access, networking, and GPU utilization for distributed robotics workloads.
- Accelerate distributed inference using NVIDIA NIM, TensorRT-LLM, vLLM, and SGLang.
- Collaborate with business, engineering, and product teams and provide technical guidance and mentorship to customers.
Requirements
- Bachelor’s degree in Computer Science, Computer Engineering, or a related field, or equivalent experience.
- 5+ years of experience in Solutions Architecture or Infrastructure Engineering, advancing AI/ML systems from proof of concept to production on private or public cloud environments.
- Experience scaling robotics workloads in areas such as 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, storage technology, workflow orchestration software, DevOps practices, and efficient GPU workload orchestration.
- Excellent communication skills for conveying technical concepts to diverse audiences.
- Preferred: experience with ROS2, Isaac Lab, Isaac Sim, GR00T, Cosmos, robotics data curation and annotation pipelines, NVIDIA Dynamo, NIM, Triton, vLLM, quantization, agentic workflows, S3, NFS, Lustre, REST, and gRPC.
Benefits
- Eligible for equity and benefits.
- Expected base salary is $152,000–$241,500 for Level 3 and $184,000–$287,500 for Level 4.
- Applications will be accepted at least until November 3, 2026.
- This posting is for an existing vacancy.
Tech Stack
Categories
Solutions Engineering
About Nvidia
Nvidia designs and sells GPUs and accelerated computing platforms for data centers, AI/ML, graphics, gaming, and automotive, monetizing through hardware, software platforms (CUDA, AI frameworks), and systems like DGX and networking. Customers include cloud providers, enterprises, researchers, and OEMs. Founded in 1993 and headquartered in Santa Clara, it is a public company traded on NASDAQ under NVDA.