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# Machine Learning Engineer and Computer Visions Engineer, Vision Products Group

- **Company:** Apple Inc.
- **Location:** Sunnyvale, CA, United States
- **Experience:** Experienced
- **Salary:** $147,400.0 - $272,100.0
- **Contract:** Permanent contract
- **Skills:** Apple IOS, Apple Mac Systems, Apple Xcode, Artificial Neural Networks, Computer Vision, C++ (Programming Language), CMake, Code Generation, Software Debugging, Distributed Computing Environment, Python (Programming Language), Machine Learning, OpenCV, Tensorflow, Sensor Fusion, Software Engineering, Pytorch, Deep Learning, Keras, Production Code, Build Tools, Machine Learning Operations, Hardware Infrastructure, Data Pipelines
- **Published:** May 29, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=7cba9cf55347adaa

## About the Role

Do you have experience in Software engineering?, Experience developing on macOS and iOS platforms

Familiarity with Apple's internal ML/CV frameworks and tools

Experience with distributed training on clusters and multi-GPU systems

Knowledge of Apple Neural Engine optimization techniques

Experience with temporal/sequential neural network architectures (RNNs, LSTMs, Transformers for video/time-series data)

Proficiency with CMake and Xcode build systems, M.S. or Ph.D. in Computer Vision, Machine Learning, Robotics, or related field; or equivalent practical experience with a proven track record of shipping products leveraging state-of-the-art Computer Vision and Machine Learning technologies

3+ years of professional software development experience with demonstrated ability to deliver high-quality, production-ready code

Expert-level proficiency in Python and C/C++

Strong software design, problem-solving, and debugging capabilities

Hands-on experience with modern ML frameworks (PyTorch, TensorFlow/Keras, PyTorch Lightning)

Solid background with Computer Vision libraries and frameworks (OpenCV, etc.)

Experience training and optimizing machine learning models for computer vision applications

Excellent communication and collaboration skills with ability to work effectively in team environments; self-motivated and quick to adapt to new technologies

Familiarity with Gen AI coding tools. Demonstrated ability to use them for design, code generation, and debugging

## Description

As a Machine Learning Engineer on our team, you'll design and implement advanced computer vision solutions that run efficiently on-device, ensuring exceptional performance while respecting user privacy. You'll work across the complete ML lifecycle-from building robust data pipelines and training deep learning models on distributed clusters to optimizing them for Apple's Neural Engine and deploying in production systems. Your work will span critical areas including localization and spatial understanding, where you'll develop systems that enable devices to perceive their position and navigate the world with precision. Your role will bridge cutting-edge research and practical engineering, requiring you to balance innovation with the real-world constraints of shipping products at scale-whether that's ensuring localization works reliably in challenging environments, handling edge cases in visual recognition, or optimizing models to run in real-time on device. Collaborating with world-class
researchers, software engineers, and product teams, you'll tackle challenging problems in visual understanding, from place recognition and scene reconstruction to temporal reasoning and multi-sensor fusion. This position offers the unique opportunity to push the boundaries of on-device machine learning, creating spatial intelligence experiences that are not only accurate and responsive but also seamlessly integrated into products that millions of people use every day.","responsibilities":"Design, train, and deploy computer vision models for localization and spatial understanding on Apple devices

Build robust data pipelines and implement distributed training workflows on multi-GPU infrastructure

Optimize deep learning models for Apple's Neural Engine, achieving real-time performance while maintaining accuracy

Solve challenging problems in visual perception including place recognition, scene reconstruction, and multi-sensor fusion

Collaborate with other teams to adapt cutting-edge techniques for production constraints and real-world deployment

Validate model performance through comprehensive testing across diverse environments and use cases


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