Multimodal LLMs Research Engineer

Apple Inc.

Sunnyvale (CA)

On-site

USD 150,400 - 277,600

Full time

14 days+
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Job summary

Apple Inc. in Sunnyvale, California is seeking exceptional researchers to advance multimodal LLMs and AI across Apple products. You will drive design, training, evaluation, and deployment of multimodal foundation models from ideation to product readiness.

The role emphasizes strong publication and patent activity, collaboration across teams, and delivering cutting‑edge computer vision and perception technologies. Competitive pay and comprehensive benefits apply.

Qualifications

  • Ph.D. with relevant research background or MS with 2+ years industry experience.
  • Publications, patents, and/or shipping relevant features.
  • Strong Python programming experience.
  • Strong PyTorch and/or JAX programming experience.
  • Ability to utilize AI code development tools to accelerate development.

Responsibilities

  • Model Design & Development: develop, implement, and enhance multimodal foundation models for MM-LLMs.
  • Model Evaluation: define data and infrastructure requirements for robust evaluation.
  • Innovation & Dissemination: publish papers and/or patents; apply knowledge to drive continuous AI and CV innovation.

Skills

Python programming
PyTorch
JAX

Education

Ph.D. with relevant research background
Master of Science with 2+ years of experience

Job description

Sunnyvale, California, United States Machine Learning and AI

We are actively seeking exceptional individuals who thrive in collaborative environments and are driven to push the boundaries of what is currently achievable with multimodal inputs and large language models. Our centralized applied research and engineering group is dedicated to developing cutting‑edge Computer Vision and Machine Perception technologies across Apple products. We balance advanced research with product delivery, ensuring Apple quality and pioneering experiences. A successful candidate will possess deep expertise and hands‑on experience across the full lifecycle of Multimodal LLM development, encompassing early ideation, data definition, model training, and fine‑tuning.

Description

We are seeking a candidate with a proven track record—demonstrated through academic research, industry contributions, or a combination of both—in developing multimodal LLMs and advanced topics such as agentic AI, reasoning, and large‑scale model evaluation. This role offers the opportunity to drive groundbreaking research projects, spanning foundational concepts to practical applications.

Responsibilities
  • Model Design & Development: Developing, implementing, and enhancing multimodal foundation models. This encompasses training or fine‑tuning MM‑LLMs from scratch or leveraging existing technologies to optimize performance and capabilities.
  • Model Evaluation: Collaborating closely with cross‑functional partners to define data and infrastructure requirements crucial for robust evaluation of model designs and developments.
  • Innovation & Dissemination: Staying at the forefront of advancements in AI, machine learning, and computer vision, and applying this knowledge to foster continuous innovation within the company. Depending on your research expertise and project scope, you will have the opportunity to publish papers and/or patents to positively impact the broader community.
Minimum Qualifications
  • Ph.D. with relevant research background, or Master of Science and a minimum of 2 years of relevant industry experience
  • Demonstrated track record through publications, patents, and/or shipping relevant features
  • Strong Python programming experience
  • Strong PyTorch and/or JAX programming experience
  • Ability to effectively utilize AI code development tools to accelerate the development process
Preferred Qualifications
  • Strong publication record in relevant venues, such as CVPR, ICCV, ECCV, NeurIPS, ICML, ICLR, etc.
  • Technical leadership experience - guiding technical efforts across diverse teams/individuals.
  • Experience in shipping MM‑LLMs in products.

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 $150,400 and $277,600, 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 seek to promote 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.

At Apple, we believe accessibility is a fundamental human right. You’ll find that idea reflected in everything here — in our culture, our benefits and our digital tools. By welcoming as many perspectives as possible, we help you build a career where you feel like you belong.

Learn about accessibility in Apple’s workplace.

Learn about reasonable accommodations for job applicants.

Apple accepts applications to this posting on an ongoing basis.

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