AMI développe des systèmes d’intelligence artificielle fondés sur des modèles du monde, dotés de mémoire, de raisonnement et de capacités de planification. L’entreprise vise des applications pour des organisations confrontées à des tâches complexes dans le monde réel.
AMI Scientist/Interns - Geometry and 3D Vision
Am I a fit — voir ma compatibilitéAMI recherche des scientifiques et stagiaires pour faire progresser la modélisation du monde, avec un focus sur la géométrie 3D du monde réel. Les missions couvrent l’apprentissage auto-supervisé, la prédiction de dynamiques à partir de vidéos, la préparation de données et l’évaluation de modèles. Le poste est basé à Paris et requiert notamment un diplôme de niveau bachelor en informatique, la maîtrise de Python et des bases en apprentissage automatique.
Repères sur AMI - Advanced Machine Intelligence
- Secteur
- Logiciels et Internet
- Type d’entreprise
- Financée par du capital-risque
- Stade
- Licorne
- Siège
- Paris
- Domaine officiel
- amilabs.xyz
- Valorisation publiée
- 3,5 Md$Source ↗
- Dernière levée
- Seed · 2026-02-01
- Montant annoncé
- 1 000 000 000 $
- Offres ouvertes
- 5
Investisseurs mentionnés
Détails de l’offre
La description complète publiée par AMI - Advanced Machine Intelligence.
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, with a specific focus on 3D geometry of the real world, 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: 3D/4D reconstruction, SLAM or SfM, depth and pose estimation, point tracking.
- Hands-on proficiency with a rendering or simulation engine (Blender, Isaac Sim, etc.), including scripted scene generation and batch rendering pipelines.
- 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)
Prérequis
- Ability to design, run, and analyze experiments independently
- Understanding of machine learning fundamentals
- large-scale training
- accelerator-based compute environments
- 3D/4D reconstruction
- SLAM
- SfM
- depth and pose estimation
- point tracking