Publié il y a 8 mois
AMI Scientist
@ AMI
Montréal, Québec
En bref
AMI is hiring an AI Scientist to advance world model research: learning from video and other high-dimensional signals, building predictive architectures, and developing model-based planning. The role is full-time and involves independent experimental research on large-scale GPU or TPU compute.
Responsabilités :
- Self-supervised learning from video and high-dimensional signals
- New architectures predicting world dynamics
- Scalable pre-processing and curation of video data
- Evaluations benchmarking world model understanding and planning
- Efficient model-based planning and reasoning algorithms
Résumé des exigences :
- Bachelor's degree or equivalent experience in computer science or related field
- Proficiency in Python
- Ability to design, run and analyze experiments independently
- Machine learning fundamentals and large-scale training
- Experience with GPU or TPU compute environments
Outils et compétences
Source et dates
Site carrière / système de candidatures · ashby
- Date publiée par l’employeur
- 2026-03-19
- Première détection par notre source
- 2026-10-08
- Mise à jour du dossier source
- 2026-10-09
Ces dates décrivent le dossier source, pas une vérification en direct du recrutement. Consultez l’offre originale.
Détails du poste
| Domaine | Recherche et sciences |
| Heures par semaine | 40 (estimé) |
| Milieu de travail | Bureau, Laboratoire |
| Position | Surtout assis |
| Exigences physiques | physique faible · ordinateur élevé |
| Langues | English |
| Formation | Baccalauréat (exigé) |
| Domaines d’études | Computer Science |
Résumé et détails rédigés par l’IA à partir de l’offre; l’offre de l’employeur fait foi.
| Champ | Valeur |
|---|---|
| Siège social | Paris |
| Offres sur Jobsy | 3 |
About AMI
We are building a new breed of AI systems that (1) understand the real world, (2) have persistent memory, (3) can reason and plan, and (4) are controllable and safe.
We are a team of scientists and engineers building frontier world model-based AI. We combine the scientific rigor of a top-tier research institute with focus on engineering excellence and execution.
We are a global company, with offices in Paris, Montreal, New York, and Singapore. Come build the future of AI with us!
About this Role
AMI believes AI agents should predict and plan using an internal model of the world — their world model. We’re looking for new team members to advance the state-of-the-art in world modeling. We believe that video is a rich and abundant source of data reflecting how the world works, and that in general models need to be able to process continuous, high-dimensional data from a variety of sensors to: (a) understand context about the current state of the physical world, (b) make predictions about how the world will evolve, possibly as a result of actions taken, and (c) plan and adapt sequences of actions to complete complex tasks, possibly in dynamic, complex environments.
You will work with a team on world model research efforts, including:
Self-supervised learning methods to efficiently learn from video and other continuous, high-dimensional signals
New architectures that efficiently learn to predict world dynamics from video and other high-dimensional signals
Scalable algorithms for pre-processing and curating video data
Evaluations for benchmarking world model understanding, prediction, and planning
Efficient algorithms for model-based planning and reasoning
Minimum Qualifications:
Bachelor’s degree or equivalent experience in Computer Science or a related field
Proficiency in Python
Ability to design, run, and analyze experiments independently
Understanding of machine learning fundamentals, large-scale training, and accelerator-based (GPU or TPU) compute environments
Preferred Qualifications:
Deep expertise in at least one of the following: self-supervised learning, video and multimodal model architectures, planning algorithms
Demonstrated record of contributing to advanced research projects via publications and/or major model releases
Experience developing evaluation frameworks for world models
Experience releasing and maintaining open-source projects
Proficiency in a deep learning framework (PyTorch or JAX)
Journal
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