CV and ML Engineer

AppleSunnyvale, CA

About The Position

Apple is where individual imaginations gather together, committing to the values that lead to great work. Every new product we build or service we create is the result of us making each other's ideas stronger. That happens because every one of us shares a belief that we can make something wonderful and share it with the world, changing lives for the better. It's the diversity of our people and their thinking that inspires the innovation that runs through everything we do. When we bring everybody in, we can do the best work of our lives. Here, you'll do more than join something, you'll add something! We are a team of computer vision and machine learning engineers building real-time 3D perception and spatial understanding technologies for current and future Apple products. The VCV org is a centralized applied research and engineering organization responsible for developing real-time on-device Computer Vision and Machine Perception technologies across Apple products. We are looking for engineers with expertise in deep learning for 3D computer vision and on-device model optimization. In this role, you will help design, build, and ship core 3D perception technologies used by millions of users across Apple's ecosystem. 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.

Requirements

  • 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

Nice To Haves

  • 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

Responsibilities

  • Developing algorithms and systems that enable 3D spatial understanding
  • Training and optimizing deep learning models
  • Building data pipelines
  • Running experiments
  • Integrating models into production software systems
  • Developing and optimizing deep learning models for 3D perception tasks
  • Building and maintaining training data pipelines
  • Improving model quality and efficiency through experimentation
  • Integrating trained models into real-time production systems
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