AMI Engineer

ami; Paris; Sur place; EUR 50 000 - 70 000; Plein temps

Résumé du poste

AMI is seeking team members in Paris to advance state-of-the-art AI systems. The role involves implementing robust methods to learn from video data and requires a Bachelor's degree in Computer Science or related field.

Key qualifications include proficiency in Python, understanding of ML fundamentals, and experience with high-performance models. Join us in shaping the future of AI!

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 computing.

Responsabilités

• Implement and optimize robust self-supervised learning methods from video data.
• Develop architectures to predict world dynamics from continuous signals.
• Create scalable infrastructure for pre-processing video data.
• Design algorithms for model-based planning and reasoning.

Connaissances

Python

Machine learning fundamentals

High-performance ML models

Deep learning frameworks (PyTorch or JAX)

Formation

Bachelor’s degree in Computer Science or related field

Outils

GPU or TPU computing environments

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