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Core ML Model Conversion Engineer
2 months ago
Position Overview:
Weekly Hours: 40
Role Summary:
Are you driven by the challenge of advancing on-device artificial intelligence and influencing the future of machine learning implementation? Become a vital part of the team responsible for Core ML, the technology that powers transformative machine learning functionalities across Apple's ecosystem.
Our innovative technology harnesses the capabilities of Apple Silicon to execute neural networks with unmatched speed and efficiency on a variety of devices including Macs, iPhones, Apple Watch, and Vision Pro.
Our team has been instrumental in the groundbreaking Apple Intelligence features recently showcased, demonstrating the advanced capabilities of on-device AI.
We enable intelligent functionalities in essential Apple applications such as Camera, Siri, Keyboard, FaceTime, and Spatial Computing, while also empowering professional-grade third-party applications to utilize the power of on-device AI.
By leveraging Apple's custom-designed CPU, GPU, and Neural Engine, we facilitate these applications in delivering exceptional AI-driven experiences with outstanding performance and efficiency.
As a pivotal member of our team, you will bridge the gap between the training of state-of-the-art deep learning models and their efficient execution on Apple devices.
Your expertise will be essential in transforming complex computational graphs from frameworks like PyTorch and JAX into optimized formats that maximize our hardware's potential.
You will focus on deploying cutting-edge models of various sizes to operate on-device with high performance, ensuring low latency, memory efficiency, and power optimization.
We are looking for a highly motivated individual with a profound understanding of machine learning models and a passion for translating advanced models from research into practical applications on-device.
If you have a proven track record in optimizing and deploying models, writing high-quality code, and delivering impactful libraries to a diverse user base, we would like to hear from you.
In this prominent role, you will collaborate with innovative teams across Apple and industry-leading external partners.
Your contributions will significantly influence the future of on-device AI, and you will play a crucial role in Apple's open-source initiatives, directly impacting the global AI developer community.
Key Responsibilities:
We are the team that develops Core ML Tools, an open-source Python library for converting PyTorch and TensorFlow models to Core ML and optimizing them for performance.
- Perform model conversion from PyTorch and other libraries to the Core ML model format.
- Run and benchmark models, understanding how computational graph representation affects execution performance on Neural Engine, GPU, and CPU.
- Proficiently set up and run open-source ML models, understanding ML pipelines and determining which components should be included in the model versus those that should be handled as pre-processing and post-processing steps.
- Add graph passes to enhance performance.
Publish examples of models converted in efficient ways (e.g., the Apple Stable Diffusion open-source library).
- Collaborate effectively with developers, both internal and external, and actively engage with the open-source CoreMLTools community on GitHub, addressing issues and contributing to discussions.
- Implement new operations and layers for neural networks.
- Enhance model optimization documentation, writing examples, tutorials, and guides.
Join us in shaping the future of on-device AI and be part of the team that's redefining what's possible with machine learning on Apple devices.
Minimum Qualifications:
BS/MS/PhD in Computer Science or Electrical Engineering
2+ years of industry experience
Strong Python programming skills (C++ is a significant advantage).
Preferred Qualifications:
Strong fundamentals in machine learning and familiarity with the latest model architectures.
Deep understanding of operations that constitute a model (e.g., gather, convolution, attention, etc.).
Proficiency in PyTorch, TensorFlow, or JAX.
Comfortable working with computational graphs and intermediate representations (compiler background is a strong plus).
Ability to profile models and analyze the impact of conversion/model representation on performance.
Experience in developing public-facing APIs (in Python or C/C++).
Passionate about engaging and collaborating with the machine learning community in open source (a track record in this area is a strong advantage).
Compensation & Benefits:
At Apple, base pay is one component of our total compensation package and is determined within a range, allowing for growth as you develop within your role.
The base pay range for this position is between $135,400 and $250,600, depending on your skills, qualifications, experience, and location.
Apple employees have the opportunity to become shareholders through participation in discretionary employee stock programs, including eligibility for restricted stock unit awards and the option to purchase Apple stock at a discount through the Employee Stock Purchase Plan.
Additional Benefits:
Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and reimbursement for certain educational expenses related to career advancement at Apple.
Additionally, this role may be eligible for discretionary bonuses or commission payments as well as relocation assistance. Learn more about Apple Benefits.Note:
Apple's 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 committed to inclusion and diversity, taking affirmative action to ensure 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.