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. Our algorithms are implemented using PyTorch. We optimize models across domains including NLP vision text generative models etc. Key responsibilities of this role are: - Setting up and/or streamlining CI and automation pipelines. Adopting the best practices and integrating with the latest Apple internal CI services for the same. - Making enhancements to the release process automating nightly builds and setting up scheduled CI runs for different levels of testing etc. - Making innovations in model testing and benchmarking (accuracy and latency) for various combinations of model types in different domains (vision text audio etc) and compression algorithms (quantization pruning palettization etc) discovering performance/accuracy trends effects of various hyper parameters etc. - Finding innovative ways to reduce test time while maintaining high quality test coverage - Passionate about the user experience and ways to improve it to fix bugs understand user pain points and actively participate in supporting users.- Developing integration of the model optimization library with other training engines and data platforms at Apple. - Keeping the code base updated to work with the latest versions of Python PyTorch numpy etc. - Set up and debug training jobs datasets evaluation performance benchmarking pipelines. Ability to ramp up quickly on new training code bases and run experiments. - 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
Bachelors in Computer Sciences Engineering or related discipline.
2 years of industry experience (including internships)
Highly proficient in Python programming
Expertise in shell programming experience with setting up and/or maintaining CI pipelines for at least one production software codebase
Good communication skills including ability to communicate with cross-functional audiences
Demonstrated ability to design user friendly and maintainable APIs
Proficiency in at least one ML authoring framework such as PyTorch TensorFlow JAX MLX
Experience in training fine tuning and optimizing neural network models
Experience in the area of model compression and quantization techniques specially in one of the optimization libraries for an ML framework (e.g. ).
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 $147400 and $272100 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 Apples 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 Apples Employee Stock Purchase Plan. Youll 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.
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