AMI Scientist/Interns - Geometry and 3D Vision

Ami; Paris; Sur place; EUR 70 000 - 110 000; Plein temps

Résumé du poste

AMI is hiring researchers to advance world model research with a focus on 3D geometry and video data. You will collaborate with scientists and engineers to push forward state-of-the-art prediction, planning, and model-based reasoning.

The role emphasizes designing and evaluating experiments, building scalable data pipelines, and contributing to open models and benchmarks in a dynamic team environment.

Qualifications

• Bachelor's degree or equivalent in Computer Science or related field.
• Proficiency in Python.
• Ability to design, run, and analyze experiments independently.
• Understanding of machine learning fundamentals, large-scale training, and accelerator-based compute environments.

Responsabilités

• Advance state-of-the-art world model research focusing on 3D geometry of the real world.
• Develop self-supervised learning methods to learn from video and high-dimensional signals.
• Design architectures to predict world dynamics from video data.
• Build scalable pre-processing and data-curation pipelines for video datasets.
• Evaluate world model understanding, prediction, and planning.

Connaissances

Python

Experiment design

Machine learning fundamentals

GPU/TPU compute

PyTorch

JAX

Formation

Bachelor's degree in Computer Science or related field

Outils

Blender

Video data processing

3D reconstruction

Description du poste

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)

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