AMI Engineer

AMI Labs; Paris; Sur place; EUR 80 000 - 120 000; Plein temps

Résumé du poste

AMI Labs in Paris, France, is hiring for a role focusing on advancing world model-based AI by predicting and planning with internal world models. You will work on self-supervised learning from video and high-dimensional signals to understand context and forecast dynamics, enabling robust planning in dynamic environments.

You will collaborate with scientists and engineers to develop scalable architectures, pre-processing pipelines for video data, and efficient inference on GPU/TPU clusters,

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 and large-scale training
• Experience with PyTorch or JAX and distributed training

Responsabilités

• Implement robust and scalable self-supervised learning methods from video and high-dimensional signals
• Develop and scale architectures to predict world dynamics from video
• Create scalable infrastructure for pre-processing and curating video data
• Design efficient algorithms for model-based planning and reasoning

Connaissances

Python proficiency

Experiment design & analysis

Machine learning fundamentals

Distributed training

Formation

Bachelor’s degree in Computer Science or related field

Outils

PyTorch

JAX

CUDA / GPU compute

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 of scientists and engineers, including:

• Implementing and optimizing robust and scalable self-supervised learning methods to efficiently learn from video and other continuous, high-dimensional signals

• Develop and scale new architectures that efficiently learn to predict world dynamics from video and other high-dimensional signals, focusing on performance and efficiency

• Scalable infrastructure and algorithms for pre-processing and curating video data

• 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:

• Strong track record of building and deploying high-performance ML models

• Experience developing, testing, and maintaining large-scale distributed systems

• Experience releasing and maintaining open-source projects

• Proficiency in a deep learning framework (PyTorch or JAX), especially for distributed training and efficient inference