Degree in Artificial intelligence- AI
Aartificial intelligence, Algorithms, CoreML, Machine learning techniques, Natural Language Processing (NLP), Optimization, Python Programming, Streaming APIs, Writing
Are you excited about the impact that optimizing deep learning models can have on enabling transformative user experiences? The field of ML compression research continues to grow rapidly and new techniques to perform quantization, pruning etc are increasingly available to be ported and adopted by the ML developer community looking to ship more models in a constrained memory budget and make them run faster. We are passionate about productizing and pushing the envelope of the state of the art model optimization algorithms, to further compress and speed up the thousands of deep learning models shipping as part of Apple internal and external apps, running locally on millions of Apple devices.
We work on a python library that implements a variety of training time and post training quantization algorithms and provides them to developers as simple to use, turnkey APIs, and ensures that these optimizations work seamlessly with the Core ML inference stack and Apple hardware. We are a small core team that collaborates heavily with researchers at Apple, ML software and hardware architecture teams and external product teams shipping state of the art optimized models on Apple devices. If you are excited about making a big impact and playing a critical role in growing the user base and driving the adoption of a relatively new library, this is a great opportunity for you.
We are looking for someone who is highly self motivated and passionate about optimizing models for on device execution. If you have a proven track record of applied deep learning research in model quantization, writing high quality code and shipping software, we strongly encourage you to apply.
Key Qualifications
We work on developing, prototyping and productizing state of the art algorithms for neural network model compression. Our algorithms are implemented using PyTorch and optimizations are geared towards efficient deployment via Core ML. We optimize models across domains, including NLP, vision, text and large generative models. Our APIs are available to Core ML users, both internal to Apple and external developers via the Core ML Tools optimization sub module. As a successful engineer in our team, you will:
* Implement latest algorithms from research papers for model compression and apply to latest model architectures such as diffusion models, large language models etc
* Set up training jobs, datasets, evaluation, performance benchmarking pipelines. Applying training time and post training compression techniques
* Understanding HW capabilities and incorporating those in optimization algorithm design / enhancement
* Build upon the latest research to create new algorithms and invent new ways of applying compression to deep learning models from different domains
* Keep up with the latest AI research and collaborate with diverse teams, both internal and external to Apple, including researchers, hardware architects, and software engineers, to co develop and implement algorithms customized for Apple hardware
* Run detailed experiments and ablation studies to profile algorithms on various models, tasks, across different model sizes
* Improving model optimization documentation, writing tutorials and guides
* Self prioritize and adjust to changing priorities and asks
Education & Experience
* BS/MS/PhD in Computer Science or Electrical Engineering
* 3+ years of industry or research experience
Additional Requirements
Pay & Benefits
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.
Headquartered in Cupertino, California, Apple Inc. is a multinational technology company that focuses on producing consumer electronics, software, and online services. It holds the distinction of being the world's largest technology company by revenue and the world's biggest company by market capitalization as of June 2022. Apple is the second-largest mobile phone manufacturer and the fourth-largest personal computer vendor by unit sales.
Shanghai, Shanghai, China
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Cupertino, CA, USA
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Seattle, WA, USA
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Seattle, WA, USA
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Cupertino, CA, USA
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Cupertino, CA, USA
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New York, NY, USA
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Cupertino, CA, USA
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Herzliya, Israel
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Cambridge, UK
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Cupertino, CA, USA
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Cupertino, CA, USA
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Cupertino, CA, USA
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Shanghai, China
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Shanghai, China
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Cupertino, CA, USA
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Seattle, WA, USA
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Sydney NSW, Australia
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Cupertino, CA, USA
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Cupertino, CA, USA
8-10 year
Shanghai, China
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Zürich, Switzerland
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Seattle, WA, USA
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Seattle, WA, USA
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Cupertino, CA, USA
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Cupertino, CA, USA
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Cupertino, CA, USA
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Cupertino, CA, USA
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Cupertino, CA, USA
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Austin, TX, USA
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Cupertino, CA, USA
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Beijing, China
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Seattle, WA, USA
10-12 year
Cupertino, CA, USA
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Cupertino, CA, USA
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Cupertino, CA, USA
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Cupertino, CA, USA
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Cupertino, CA, USA
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Cupertino, CA, USA
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Cupertino, CA, USA
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Seattle, WA, USA
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Seattle, WA, USA
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Beijing, China
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Cupertino, CA, USA
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Cupertino, CA, USA
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Nanshan, Shenzhen, Guangdong Province, China
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Zürich, Switzerland
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Cambridge, MA, USA
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Cupertino, CA, USA
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Nanshan, Shenzhen, Guangdong Province, China
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Zürich, Switzerland
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Beijing, China
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Cupertino, CA, USA
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Austin, TX, USA; Campbell, CA, USA; Cerritos, CA, USA; Costa Mesa, CA, USA; Cupertino, CA, USA; East Palo Alto, CA, USA; Irvine, CA, USA; Los Angeles, CA, USA; Los Gatos, CA, USA
4-6 year
Culver City, CA, USA; San Diego, CA, USA; Seattle, WA, USA
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New York, NY, USA; San Diego, CA, USA; Seattle, WA, USA
4-6 year
Cupertino, CA, USA; New York, NY, USA; San Francisco, CA, USA; Seattle, WA, USA
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Boulder, CO, USA; Cupertino, CA, USA; Seattle, WA, USA
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Austin, TX, USA; Cupertino, CA, USA
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Cupertino, CA, USA; San Francisco, CA, USA; Seattle, WA, USA
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Boulder, CO, USA; Cupertino, CA, USA; Seattle, WA, USA
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Culver City, CA, USA; New York, NY, USA; Raleigh, NC, USA
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Cupertino, CA, USA; Seattle, WA, USA
6-8 year
Cupertino, CA, USA; Seattle, WA, USA
8-10 year
Cupertino, CA, USA; Seattle, WA, USA
6-8 year
Austin, TX, USA; Seattle, WA, USA
2-4 year
Cupertino, CA, USA
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Cupertino, CA, USA; Seattle, WA, USA
6-8 year
Cupertino, CA, USA; Seattle, WA, USA
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Cupertino, CA, USA; Seattle, WA, USA
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Beijing, China; Shanghai, China
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Cupertino, CA, USA; Seattle, WA, USA
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Cupertino, CA, USA; Seattle, WA, USA
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Cupertino, CA, USA; New York, NY, USA
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Cupertino, CA, USA; Seattle, WA, USA
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Cupertino, CA, USA; Seattle, WA, USA
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Cupertino, CA, USA; Seattle, WA, USA
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Cupertino, CA, USA; Seattle, WA, USA
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Cupertino, CA, USA; Seattle, WA, USA
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Cupertino, CA, USA; Seattle, WA, USA
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Cupertino, CA, USA; Seattle, WA, USA
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Cupertino, CA, USA; Seattle, WA, USA
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Cupertino, CA, USA; Seattle, WA, USA
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