Member of Technical Staff - Simulation
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Before you apply
LocationToronto
Work modehybrid
Typefull-time
SeniorityLead
DepartmentTechnical Staff
Company size8+ people
PostedAug 19, 2026 · 2mo ago
Verified live3d ago
At a glanceSummarised by Seekless from the posting.
Bachelor's degree or equivalent hands-on experience in Computer Science, Computer Graphics, Robotics, or a related technical field
Experience building or substantially extending a physics engine or simulation framework (Newton, MuJoCo, PhysX, or something proprietary)
Strong C++ and Python skills and experience writing GPU code in CUDA, NVIDIA Warp, or an equivalent data-parallel framework
Fluency in 3D content pipelines (OpenUSD, glTF, meshes, materials, coordinate frames, units, inertias) and their intricacies
Ability to measure simulation fidelity and close quantified gaps between simulators and the hardware they model
Development experience with OpenUSD tooling or Omniverse Kit extensions
Scalable procedural content generation skills (Infinigen, Houdini, Blender Geometry Nodes)
Experience with differentiable simulation or gradient-based system identification
Experience building 3D Gaussian splatting or NeRF reconstruction pipelines with simulatable outputs
Sensor modeling skills using real device characterization data (lidar, radar, event cameras, tactile arrays)
Contributions to open-source simulation projects (Newton, MuJoCo Warp, Isaac Lab, mjlab)
Skills
C++
Python
CUDA
NVIDIA Warp
Isaac Lab
Carla
Gymnasium
OpenUSD
URDF
MJCF
glTF
Newton
MuJoCo
PhysX
Infinigen
Houdini
Blender Geometry Nodes
Omniverse Kit
Member of Technical Staff - Simulation
About Us
Veeda AI is building the next generation of multimodal foundation world models for Physical AI. We’re a small, fast-moving team of engineers and researchers from leading AI labs, tackling some of the most challenging problems at the intersection of AI, robotics, and embodied intelligence. If you’re excited about pushing the boundaries of what’s possible with Physical AI, you’ll have the opportunity to make an outsized impact from day one.
Responsibilities
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Simulator integration: Help us connect our world models to existing simulator APIs that customers are familiar with (Isaac Lab, Carla, etc).
•
Harness engineering: Rethink “classical” to become a physical AI equivalent of an LLM coding harness.
•
Synthetic data generation: Own the moment when the world model and policy close the loop, collect success/failure cases of both algorithms.
•
Scene & Asset Pipelines: Build procedural scene generation and articulated asset authoring on OpenUSD, URDF, and MJCF, with automated convex decomposition, inertial-property assignment, and the QA that stops a broken asset reaching a training run.
•
Throughput & Determinism: Help us keep rollouts replayable under a fixed seed and configuration so a regression can be bisected.
•
Environment API & Fidelity: Own the interface policy training runs against (Gymnasium-style APIs, Isaac Lab managers) and the regression benchmarks that score both task success and divergence from real-hardware traces.
Requirements
•
Bachelor’s degree or equivalent hands-on experience in Computer Science, Computer Graphics, Robotics, or a related technical field.
•
Experience building or substantially extending a physics engine or simulation framework (Newton, MuJoCo, PhysX, or something proprietary).
•
Strong C++ and Python skills and experience writing GPU code in CUDA, NVIDIA Warp, or an equivalent data-parallel framework.
•
Fluency in 3D content pipelines (OpenUSD, glTF, meshes, materials, coordinate frames, units, inertias) and their intricacies.
•
Ability to measure simulation fidelity and close quantified gaps between simulators and the hardware they model.
Nice to Have
•
Development experience with OpenUSD tooling or Omniverse Kit extensions.
•
Scalable procedural content generation skills (Infinigen, Houdini, Blender Geometry Nodes).
•
Experience with differentiable simulation or gradient-based system identification.
•
Experience building 3D Gaussian splatting or NeRF reconstruction pipelines with simulatable outputs.
•
Sensor modeling skills using real device characterization data (lidar, radar, event cameras, tactile arrays).
•
Contributions to open-source simulation projects (Newton, MuJoCo Warp, Isaac Lab, mjlab).