Publié il y a 2 mois
Member of Technical Staff - World Models
@ Veeda AI
Toronto, Ontario
En bref
Veeda AI is hiring a Member of Technical Staff to build multimodal foundation world models for Physical AI. The role designs, trains and scales generative and predictive models across visual and spatial data, with a strong focus on evaluation and experimentation. The posting requires a PhD or equivalent experience and hands-on distributed training with PyTorch.
Responsabilités :
- Design, train and scale generative and predictive models
- Develop multimodal learning and control methods
- Improve sequence modeling consistency and robustness
- Explore post-training and efficiency techniques
- Build evaluations and run controlled experiments
Résumé des exigences :
- PhD in Computer Science, Engineering or related field, or equivalent experience
- End-to-end training of foundation models
- Strong PyTorch and distributed training skills
- Independent design and analysis of ML experiments
- Experience developing model evaluations
Outils et compétences
Source et dates
Site carrière / système de candidatures · ashby
- Date publiée par l’employeur
- 2026-09-07
- 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 | Doctorat (exigé) |
| Domaines d’études | Computer Science, Engineering |
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 – World Models
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
Model Research & Development: Design, train, and scale generative and predictive models across visual and spatial modalities.
Multimodal Learning & Control: Develop methods for learning from diverse data sources and incorporating conditioning signals into model behavior.
Sequence Modeling: Improve consistency, robustness, and generalization in models of complex temporal and spatial structure.
Post-Training & Efficiency: Explore post-training and model optimization techniques to improve quality, controllability, and computational efficiency.
Evaluation & Experimentation: Develop rigorous evaluations, conduct controlled experiments, and use findings to guide modeling and data decisions.
Research Collaboration: Work closely with data, systems, and robotics engineers to translate research ideas into reliable capabilities.
Requirements
PhD degree in Computer Science, Engineering, or a related technical field, or equivalent experience.
Experience training machine learning foundation models end to end, with strong PyTorch skills and hands-on experience in distributed training.
Ability to independently design, execute, and analyze machine learning experiments, from hypothesis through ablation to conclusion.
Experience developing evaluations that reveal model limitations and inform research decisions.
Nice to Have
Strong publication record or substantial contributions to research on image, video, 3D, or multimodal models.
Experience with learned representations, compression, or tokenization for high-dimensional data.
Experience with conditional generation, temporal consistency, or long-context modeling.
Experience with reinforcement learning, model-based learning, or embodied AI.
Experience with post-training, distillation, or efficient inference for generative models.
Experience working with large-scale, heterogeneous visual or sensor datasets.
Contributions to open-source machine learning projects or research infrastructure.
Journal
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