Senior Solutions Architect – Simulation Solutions 3d Reconstruction

NVIDIA NVIDIA · Semiconductors · Santa Clara, CA

This role focuses on developing and scaling AI platforms for simulation and 3D reconstruction, particularly within the Omniverse ecosystem. The Senior Solutions Architect will act as a technical advisor, prototype solutions, implement intricate technical systems, provide technical enablement, and advocate for partner needs. The role requires expertise in AI, systems knowledge, autonomous systems, simulation, generative AI, Python, C++, DL/RL frameworks, computer vision, and 3D reconstruction.

What you'd actually do

  1. Operate as a technical advisor and problem solver with partner engineering teams, collaborating on architecture, code, and integration for Omniverse and AI-enabled solutions.
  2. Actively prototyping to develop deep expertise in NVIDIA Cosmos, Omniverse Platforms, NuRec and related technologies (APIs, USD, NIMs, Blueprints) through hands-on technical integration.
  3. Implement intricate technical solutions with partners—defining objectives, architecture, landmarks, and delivery plans while contributing code samples, architecture diagrams, and hands-on engineering support.
  4. Provide technical enablement resources like workshops, reference architectures, and integration guides to speed up adoption and standard processes while collaborating with engineering and leadership teams across partner organizations to identify goals, resolve technical challenges, and align on architecture and solution direction.
  5. Advocate for partner technical needs within NVIDIA—providing actionable feedback to influence product roadmaps and future technology direction while supporting product launches and go-to-market activities, ensuring seamless integration and technical excellence in customer-facing materials.

Skills

Required

  • Master’s or Ph.D. in Computer Science, Electrical/Computer Engineering, Artificial Intelligence, or a related field (or equivalent experience)
  • 8+ years of hands-on experience in a technical AI role, with emphasis on autonomous systems, simulation, or generative AI.
  • Programming expertise in Python and C++
  • solid software design and debugging experience on Linux
  • a deep understanding of Autonomous Vehicle systems, including sensors, dynamics, perception, prediction, planning, and control.
  • Hands-on experience with DevOps tools (GitLab, Docker, Kubernetes)
  • scalable distributed systems
  • Deep Learning (DL) and Reinforcement Learning (RL) frameworks experience such as PyTorch or JAX.
  • Expertise in computer vision and 3D reconstruction technologies.
  • Excellent communication, collaboration, and presentation skills

Nice to have

  • Hands-on experience with LiDAR, radar, camera, IMU, and other sensor modalities.
  • Familiarity with NVIDIA Cosmos, NuRec, Isaac Sim, Isaac Lab, and Omniverse for physical AI simulation and synthetic data generation.
  • Strong GPU optimization and profiling expertise using Nsight Systems and Nsight Compute.
  • CUDA programming experience, model quantization, and inference acceleration.

What the JD emphasized

  • 8+ years of hands-on experience in a technical AI role
  • solid software design and debugging experience on Linux
  • deep understanding of Autonomous Vehicle systems

Other signals

  • AI platform development
  • simulation and AI platforms
  • 3D Neural Reconstruction
  • Generative Video models
  • Omniverse
  • inference optimization
  • autonomous simulation
  • Deep Learning (DL) and Reinforcement Learning (RL) frameworks
  • computer vision and 3D reconstruction technologies