AIML - Senior Software Engineer, Model Optimization Library, On-Device Machine Learning

Are you excited about the impact that compressing 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.

While there are thousands of ML models across Apple internal and external apps, running locally on millions of Apple devices, only a small fraction of these currently make use of such optimization techniques.

Bridging this gap is the mission of this team. 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 deployment, ML compiler, and hardware architecture teams.

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 framework, this is a great opportunity for you.

We are looking for someone who is highly self-motivated. If you are passionate about writing modular, extensible code, simple to use, clean APIs, and have a proven track record of shipping software that has been adopted by a large base of developers, we strongly encourage you to apply for this role.

In order to make an application, simply read through the following job description and make sure to attach relevant documents.

Description

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.
• Set up training jobs, datasets, evaluation, performance benchmarking pipelines.
• Run detailed experiments to profile algorithms on various models and across different sizes and maintaining model cards.
• Collaborate with ML practitioners across the company to co-develop and implement algorithms customized for Apple hardware.
• Manage Python releases and API backward compatibility.
• Provide user support via various channels including engagement via open source Github.
• Expand documentation with examples and benchmark data to drive user adoption and address user pain points.
• Self-prioritize and adjust to changing priorities and asks.
• Be a team player who enjoys doing things that make the overall project successful and help others in the team excel. This includes working on detailed reviews of PRs and technical docs, bug fixes, test infra, etc.

Minimum Qualifications

• Expertise with Python.
• 4+ years industry experience.
• Proven track record of delivering and maintaining high quality production software.
• Demonstrated ability to design user-friendly and maintainable APIs.
• Excellent technical communication skills.
• Proven track record of mentoring and leading execution of complex features via planning, effective delegation, and continuous tracking across multiple sprint cycles.
• Ability to collaborate effectively and excel in projects involving cross-functional teams.
• Knowledge of machine learning pipeline, from data set up, data processing, training models and evaluation.
• Demonstrated ability to learn quickly and grasp ML concepts, architectures, and optimization algorithms.

Preferred Qualifications

• Expertise with PyTorch, TF or JAX (preferred).
• Experience with model compression and quantization (preferred).
• BS / MS / PhD in Computer Science or Electrical Engineering.

Pay & Benefits

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 $143,100 and $264,200, 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 take 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.

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