Technical Lead - Simulation Engineer

Lead the daily technical execution of a 6-person simulation team, assigning sprint tasks, conducting code reviews, and resolving technical blockers across distributed workstreams.

Architect and develop core simulation platform components hands-on using NVIDIA Omniverse, OpenUSD, Nucleus, and Isaac Sim with Python and C++.

Integrate cross-functional engineering tracks, connecting cloud GPU infrastructure, scenario orchestration frameworks (ROS2), rendering/sensor models, and automated QA suites into a unified platform.

Build and optimize 3D asset ingestion pipelines, multi-GPU rendering throughput, and real-time physics simulation performance.

Standardize and drive AI-native engineering practices across the team, leveraging AI-assisted coding tools and agentic workflows for rapid development, testing, and automated scenario generation.

Job Requirements - Technical Leadership & Delivery: 5+ years of hands-on software development experience with at least 1-2 years serving in a technical lead, team lead, or sprint coordination capacity, guiding developers and translating project roadmaps into actionable sprint deliverables. NVIDIA Omniverse Ecosystem: Proven hands-on production experience architecting and implementing solutions within the NVIDIA Omniverse platform, including OpenUSD (Universal Scene Description), Omniverse Nucleus, custom Kit Extensions, and Isaac Sim. Core Languages: Advanced programming proficiency in Python and solid working proficiency in C++ for building high-performance simulation modules and extensions. Cross-Discipline Simulation Competency: Demonstrated working knowledge and ability to guide technical integration across core simulation tracks: Distributed GPU infrastructure, containerization, and orchestration (DGX, Ray). Scenario generation and robotics middleware (ROS2, DDS, SIL/HIL test harnesses). Physics and rendering simulation (Omniverse RTX, PhysX, CUDA, synthetic sensor modeling for Camera/LiDAR/Radar). Automated testing and verification. Platform runtimes and SDK development (backend APIs, build/release tooling, distributed systems). AI-Native Engineering: Practical, daily experience utilizing AI-assisted developer workflows (LLM code generation, agentic development tools, and automated testing/debugging tools) to accelerate delivery. Desired Skills & Experience - Alternative Engine Experience: Prior hands-on experience building simulation or rendering pipelines in Unreal Engine 5 (UE5). Autonomous Systems & Sensor Modeling: Domain background in robotics, autonomous vehicles (AV), or ADAS, specifically building synthetic data generation pipelines for Camera, LiDAR, or Radar perception systems. Large-Scale GPU Cluster Orchestration: Practical experience configuring and optimizing distributed batch jobs using Ray, Slurm, or NVIDIA DGX systems. Hardware-in-the-Loop Integration: Direct exposure to SIL/HIL testing environments, hardware interface testing, or real-time simulation hardware. Build Systems & Tooling: Familiarity with modern large-scale C++ build and packaging systems such as CMake or Bazel. Generative AI for Simulation: Hands-on experience integrating foundation models/LLMs directly into procedural generation pipelines (e.g., natural language-to-scenario generation or synthetic edge-case injection).

skills:

AWS,AI,QA Automation,automated testing,Build Systems,C++,CMake,code generation,containerization,distributed systems,Docker,Generative AI,GPU infrastructure,hardware interface,Hardware-in-the-Loop,Isaac Sim,Kubernetes,LLM,LLMs,LiDAR,Azure,middleware,NVIDIA Omniverse,CUDA,development tools,proficiency in Python,real-time simulation,Slurm,debugging tools,software development,configuring,technical integration,Unreal Engine 5,backend APIs,high-performance,ADAS,Autonomous Systems,autonomous vehicles,Advanced programming,Infrastructure,KPI,packaging,Modeling,Physics,Platform Engineer,Radar,robotics,Scenario generation,Sensor,Simulation,Technical Leadership,technical direction,testing,tooling,workflows