Machine Learning Engineer and Computer Visions Engineer, Vision Products Group

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.

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

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

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

Join our machine learning team at Apple to develop computer vision and localization technologies that help devices understand their place in the world. We're seeking a talented Machine Learning Engineer who excels at transforming research innovations into production-ready solutions, tackling the full spectrum from training large-scale models to optimizing them for real-time, on-device performance. If you're passionate about solving hard problems in spatial intelligence—from challenging real-world environments to privacy-preserving design—this is your opportunity to create experiences that millions of people use every day

At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $147,400 and $272,100, and your base pay will depend on your skills, qualifications, experience, and location.

Apple employees also have the opportunity to become an Apple shareholder through participation in Apple’s discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple’s Employee Stock Purchase Plan. You’ll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses — including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits

Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant

At Apple, we believe accessibility is a fundamental human right. You’ll find that idea reflected in everything here — in our culture, our benefits and our digital tools. By welcoming as many perspectives as possible, we help you build a career where you feel like you belong.

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Apple accepts applications to this posting on an ongoing basis.