Publié il y a 3 mois
Member of Technical Staff - Simulation
@ Veeda AI
Toronto, Ontario
En bref
Veeda AI is hiring a Member of Technical Staff for simulation work on multimodal foundation world models for Physical AI. The role covers simulator integration, synthetic data generation, scene and asset pipelines, and environment APIs and fidelity benchmarks. The posting states a full-time employment type but no pay, location, or work arrangement.
Responsabilités :
- Connect world models to existing simulator APIs
- Build procedural scene and articulated asset pipelines
- Generate synthetic success and failure data
- Keep simulation rollouts replayable under fixed seeds
- Own environment APIs and fidelity regression benchmarks
Résumé des exigences :
- Bachelor's degree or equivalent hands-on experience
- Experience building a physics engine or simulation framework
- Strong C++ and Python skills
- GPU programming in CUDA, NVIDIA Warp, or equivalent
- Expertise in 3D content pipelines and fidelity measurement
Outils et compétences
Source et dates
Site carrière / système de candidatures · ashby
- Date publiée par l’employeur
- 2026-08-19
- Première détection par notre source
- 2026-10-08
- Mise à jour du dossier source
- 2026-10-22
Ces dates décrivent le dossier source, pas une vérification en direct du recrutement. Consultez l’offre originale.
Détails du poste
| Niveau | Intermédiaire |
| Domaine | Développement logiciel |
| Heures par semaine | 40 (estimé) |
| Milieu de travail | Bureau |
| Position | Surtout assis |
| Exigences physiques | physique faible · ordinateur élevé |
| Langues | English |
| Formation | Baccalauréat (préféré) |
| Domaines d’études | Computer Science, Computer Graphics, Robotics |
Résumé et détails rédigés par l’IA à partir de l’offre; l’offre de l’employeur fait foi.
Veeda AI
Profil d’entreprise sauvegardé
Renseignements historiques provenant d’un profil The Jobs API sauvegardé (champs LinkedIn/Crunchbase). Ils ne sont pas vérifiés en temps réel; les chiffres peuvent avoir changé. Les valeurs manquantes restent inconnues.
Scaling Physical AI through Interactive Learning in Simulated Reality
Description complète de l’entreprise
Scaling Physical AI through Interactive Learning
- Personnes associées sur LinkedIn
- 3
- Autres noms enregistrés
- Veeda AI
- Le profil indique une agence de recrutement
- Non
Scaling Physical AI through Interactive Learning
| Champ | Valeur |
|---|---|
| Secteur | Artificial Intelligence |
| Taille | 11-50 employees |
| Type d’organisation | Privately Held |
| Fondée en | 2026 |
| Offres sur Jobsy | 10 |
| Voir la page |
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
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).
Journal
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