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 AI/ML workloads. This role offers an outstanding chance to build within the rapidly growing field of Robotics AI & Simulation. You’ll work closely with our product management, engineering, and business teams to drive the adoption of NVIDIA's groundbreaking Physical AI technologies with our key ecosystem partners!
What you'll be doing:
Support customers in building scalable and observable GPU-accelerated pipelines for key robotics workloads using Kubernetes, cloud-native technologies, and NVIDIA frameworks (OSMO, Dynamo) across heterogeneous infrastructure.
Develop a deep understanding of robotics workloads scaling and help translate those into optimal architectures for partners
Collaborate with DevOps teams to orchestrate data preprocessing, distributed training and inference workloads to optimize job scheduling, costs, storage access, and networking across hybrid and multi-cloud Kubernetes environments (e.g., AWS, Azure, GCP, on-prem).
Accelerate inference pipelines using NVIDIA NIM, TensorRT-LLM, vLLM, SGLang, and other engines to enable seamless, disaggregated inference architectures.
Collaborate with multi-functional teams (business, engineering, product) and provide technical mentorship to customers implementing Physical AI at scale.
What we need to see:
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 with scaling Robotics workloads in one or more areas, such as VLM/VLA model training, model inference, robot learning and simulation, data generation.
Strong 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 using the NVIDIA GPU Operator and MIG.
Excellent communication skills to convey technical concepts to diverse audiences.
BS in Computer Science, Computer Engineering, or a related field, or equivalent experience.
Ways to stand out from the crowd:
Proficiency with robotics frameworks (e.g., ROS2) and NVIDIA simulation and AI platforms such as Isaac Lab, Isaac Sim or Cosmos.
Experience with AI/ML training workflows and distributed job orchestration using tools like Ray.
Deep expertise of transformer networks and experience deploying NVIDIA inference technologies (Dynamo, NIM, Triton, vLLM) using acceleration techniques like quantization.
Experience with large scale data curation techniques and optimization
Broad technical expertise across networking, compute, and storage systems (e.g., S3, NFS, Lustre), with hands-on experience building and debugging APIs (REST, gRPC) as well as relevant certifications such as NVIDIA Certified AI Engineer, Certified Kubernetes Administrator (CKA), or Cloud Solutions Architect.
Widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family www.nvidiabenefits.com/
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4.You will also be eligible for equity and benefits.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.Top Skills
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
