Multi-Modal LLM Research Engineer, Model Optimization and Algorithms Development

Summary

Posted: Feb 25, 2025

Weekly Hours: 40

Role Number:200592777

The System Intelligence and Machine Learning (SIML) organization at Apple is looking for a Multi-Modal LLM Research Engineer to help shape the future of on-device Apple Intelligence. In this role, you will work at the intersection of large language models, neural network optimizations, and algorithm development, driving innovations that enhance real-world AI experiences for millions of users.

Description

As part of a collaborative team of deep learning experts and software engineers, you will explore the optimal trade-offs between model quality and efficiency, ensuring that innovative Multi-Modal LLMs can be seamlessly deployed on-device. You will translate the latest research into practical engineering solutions or innovate novel technologies, shaping key decisions on on-device model deployment and real-world performance. Working closely with various teams at Apple, you will help design Multi-Modal LLM architectures, refine training paradigms for real-world applications, and develop software optimized for emerging hardware architectures-potentially even influencing future hardware designs. If you want to be part of a science- and results-driven team and are comfortable embracing new challenges in a fast-paced, iterative environment, we'd love to hear from you. Your research and development will directly shape the next generation of Apple Intelligence experiences!

• Masters, or Ph.D. in Computer Science, or Computer Engineering; similarly related fields, or comparable professional experience.
• Experience on developing/optimizing/training large language models (LLMs), or large computer vision models, or generative AI models.
• Proven track record to drive scientific investigations and experiments and overcome obstacles and uncertainty in a research environment.
• Excellent communication and collaboration skills, and have the ability to work hands-on in multi-functional teams.
• Solid mathematical foundation of machine learning and deep learning techniques.
• Strong programming skills in Python, solid understanding of C++.
• Proficiency in at least one deep learning framework (e.g., PyTorch, Keras, TensorFlow, JAX).

• Strong background in research and innovation, demonstrated through publications in top-tier journals or conferences, patents, or impactful industry experience.
• Experience with network optimization algorithms, e.g. quantization and compression, sparsification, knowledge distillation, or neural architecture search.
• Deep understanding of computer systems and the interactions between HW and SW.

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.