Senior Simulation Infrastructure Engineer

We are seeking a Senior Simulation Infrastructure Engineer to join a simulation engineering pod supporting the migration of an autonomy simulation platform to NVIDIA Omniverse and Isaac Sim for a global heavy-equipment manufacturer that is scaling autonomy, robotics and physical AI. In this role, you will own the GPU infrastructure the simulation platform runs on, working with our technical lead, the pod’s build and platform tooling engineer and the client’s simulation engineers to run large simulation campaigns reliably and efficiently. Your work will decide how many simulations the client can run, and how fast. Responsibilities - Simulation Infrastructure Ownership: Own the GPU compute, Kubernetes clusters, containers and pipelines that the simulation platform runs on, including NVIDIA DGX systems. - GPU Campaign Execution: Make large simulation campaigns run reliably and efficiently on GPU, from workload scheduling to GPU optimization. - Infrastructure as Code & CI/CD: Automate provisioning and deployment with Terraform, GitHub Actions and Jenkins. - Observability & Capacity Planning: Set up metrics, logs, tracing, resource scheduling and capacity planning for compute-heavy simulation workloads. - Shared Pipelines: Work with the pod’s build and platform tooling engineer on shared CI/CD pipelines. Requirements - Commercial experience in DevOps, MLOps or infrastructure engineering for compute-heavy workloads, at a senior level. - Containers & Orchestration: Production experience with Kubernetes and Docker on Linux. - Infrastructure as Code & CI/CD: Hands-on experience with Terraform and CI/CD tools such as GitHub Actions and Jenkins. - GPU Infrastructure: Proven experience scheduling GPU workloads, optimizing GPU usage and planning capacity. - Cloud Platforms: Working experience with at least one major cloud, either AWS or Azure. - Observability: Experience building metrics, logging and tracing for compute-heavy workloads. - MLOps at Scale: Experience operating large batch or distributed workloads in an MLOps-style setup. Nice to have - NVIDIA DGX: Hands-on experience with NVIDIA DGX systems. - Distributed Compute: Experience with Ray or other distributed-compute frameworks. - GPU Rendering Hosting: Experience hosting Omniverse / Nucleus or other GPU rendering workloads. - Hybrid Infrastructure: Experience running hybrid cloud and on-premise GPU environments. We offer - Opportunity to work on bleeding-edge projects - Work with a highly motivated and dedicated team - Competitive salary - Flexible schedule - Benefits package - medical insurance, sports - Corporate social events - Professional development opportunities - Well-equipped office About Us Grid Dynamics (NASDAQ: GDYN) is a leading provider of technology consulting, platform and product engineering, AI, and advanced analytics services. Fusing technical vision with business acumen, we solve the most pressing technical challenges and enable positive business outcomes for enterprise companies undergoing business transformation. A key differentiator for Grid Dynamics is our 8 years of experience and leadership in enterprise AI, supported by profound expertise and ongoing investment in data, analytics, cloud & DevOps, application modernization and customer experience. Founded in 2006, Grid Dynamics is headquartered in Silicon Valley with offices across the Americas, Europe, and India.