Job description

You will work on cutting-edge computer vision and machine learning problems, developing algorithms and systems that enable 3D spatial understanding. This includes training and optimizing deep learning models, building data pipelines, running experiments, and integrating models into production software systems. You will be responsible for developing and optimizing deep learning models for 3D perception tasks, building and maintaining training data pipelines, improving model quality and efficiency through experimentation, and integrating trained models into real-time production systems. As a member of a fast-paced team, you have the unique and rewarding opportunity to shape upcoming products that will delight and inspire millions of people every day. Master's or equivalent practical experience, in Computer Science, Computer Vision, Machine Learning, or related technical field Experience in deep learning with demonstrated work in 3D vision or geometric deep learning Proficiency in Python and in a modern deep learning framework such as PyTorch or JAX Experience with rapid prototyping, reproduction, and validation of research ideas Strong mathematical foundations in machine learning, computer vision, or related fields Experience with foundation model architectures and training methodologies Experience working effectively in a multi-functional, collaborative environment PhD, or equivalent practical experience, in Computer Science, Machine Learning, Computer Vision, or a related technical field Demonstrated expertise in deep learning, with either: A publication record in relevant conferences (e.g., NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, COLM, etc), or a strong track record of applying deep learning techniques to real-world products Experience with large-scale distributed training and model parallelism Familiarity with 3D computer vision concepts: multi-view geometry, depth sensing, camera models, or 3D reconstruction Experience with training data curation and pipeline engineering Experience with model optimization for production deployment Proficiency in C++ or experience integrating ML models into performance-critical systems Strong communication skills and ability to present research findings to both technical and non-technical audiences

Requirements

Must-haves

Master's or equivalent practical experience, in Computer Science, Computer Vision, Machine Learning, or related technical field
Experience in deep learning with demonstrated work in 3D vision or geometric deep learning
Proficiency in Python and in a modern deep learning framework such as PyTorch or JAX
Experience with rapid prototyping, reproduction, and validation of research ideas
Strong mathematical foundations in machine learning, computer vision, or related fields
Experience with foundation model architectures and training methodologies
Experience working effectively in a multi-functional, collaborative environment
PhD, or equivalent practical experience, in Computer Science, Machine Learning, Computer Vision, or a related technical field
Experience with large-scale distributed training and model parallelism
Familiarity with 3D computer vision concepts: multi-view geometry, depth sensing, camera models, or 3D reconstruction
Experience with training data curation and pipeline engineering
Experience with model optimization for production deployment
Proficiency in C++ or experience integrating ML models into performance-critical systems
Strong communication skills and ability to present research findings to both technical and non-technical audiences

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

machine learningpythonml

Platform: apple
Effort: medium

Benefits

Benefits detected in the listing.

Vision