Role at a glance
- Job function
-
AI & Data AI Research & Applied Science
- Salary
- $184.7K – $324.8K/yr
- Location
- Cupertino, California, United States
- Experience
- Minimum Qualifications PhD or MS Computer Science, Engineering, or a related field with a focus on machine learning Strong research skills with first author publications in top tier ML conferences Expert-level knowledge of SOTA in large auto-regressive transformer models, multi-modal encoders, and representation learning. Experience with multimodal large language models (LLMs) Strong programming skills in Python, maintaining ML code bases grounded in software engineering principles. Preferred Qualifications PhD in Machine Learning Proven track record of deploying innovative ML technologies in production. Familiarity with developing ML for resource-constrained devices. Experience working with large cross-functional and diverse teams.
- Education
- PhD or MS Computer Science, Engineering, or a related field with a focus on machine learning
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Role Summary
The Multimodal AI Applied Scientist develops multimodal scene-understanding technology using visual and audio data, including multimodal large language models. The role spans model architecture, training, and deployment, as well as creating human-centric experiences and production-integrated ML solutions.
What You'll Do
- Design, train, and deploy large-scale multimodal LLMs across the model lifecycle.
- Develop and demonstrate human-centric user experiences using large foundation models.
- Create scalable ML models and APIs that integrate with production pipelines and training infrastructure.
- Collaborate with partner teams to build, iterate on, and adapt solutions.
Generated from the employer's posting. Verify important details before applying.
View full postingQualifications
PhD or MS in Computer Science, Engineering, or a related field focused on machine learning; first-author publications in top-tier ML conferences; expert-level knowledge of state-of-the-art autoregressive transformer models, multimodal encoders, and representation learning; experience with multimodal LLMs; strong Python programming skills and software-engineering practices for ML codebases.
Required
- PhD or MS Computer Science, Engineering, or a related field with a focus on machine learning
- Strong research skills with first author publications in top tier ML conferences
- Expert-level knowledge of SOTA in large auto-regressive transformer models, multi-modal encoders, and representation learning.
- Experience with multimodal large language models (LLMs)
- Strong programming skills in Python, maintaining ML code bases grounded in software engineering principles.
Preferred
- PhD in Machine Learning
- Proven track record of deploying innovative ML technologies in production.
- Familiarity with developing ML for resource-constrained devices.
- Experience working with large cross-functional and diverse teams.
Original job description
Content provided by the employer
Original job description
Content provided by the employer
Summary
Apple's System Intelligence and Machine Learning (SIML) team is seeking a Multimodal AI applied scientist to drive the future of multimodal scene understanding and human-centric device interaction. At the heart of this effort, you will develop multimodal LLMs designed to perceive complex environments and understand nuanced human behaviors, preferences, and interactions. This role offers a rare opportunity to join a leading applied research team known for its foundational contributions to Apple Intelligence, where you will work across the entire generative model lifecycle, spanning novel architecture design, model training, and deployment.
Description
We are looking for an applied scientist with deep skills in ML and generative modeling to architect, train, and deploy multimodal scene understanding technology that can understand scene from visual and audio data. You will quickly build and demonstrate new user experiences using large foundation models, developing innovative capabilities while partnering with cross-functional teams and iterating rapidly in a dynamic environment.
Your work will advance human interaction and scene understanding modeling across the stack, from system-level architecture to core ML algorithms. Among the many challenges you will address are modeling user behaviors and preferences through device and environmental interactions, retrieving nuanced insights from historical context, handling deeply interleaved streaming data, reasoning across diverse temporal horizons, designing memory systems for long-term adaptation, and learning semantically rich representations for open-ended downstream applications.
You will also be responsible for delivering ML models and solutions that can be readily integrated into production pipelines, such as APIs for production-ready models and algorithms built directly into our training infrastructure.
Responsibilities
Design, train, and deploy large-scale multimodal LLMs, owning the entire lifecycle from initial architecture to final deployment within the constraints.
Implement and demonstrate novel, human-centric user experiences by applying the capabilities of large foundation models.
Create robust, scalable ML models and APIs that can be well-integrated into Apple's production pipelines and training infrastructure.
Work closely with partner teams to build, iterate, and adapt innovative solutions in a dynamic, product-focused environment.
Minimum Qualifications
PhD or MS Computer Science, Engineering, or a related field with a focus on machine learning
Strong research skills with first author publications in top tier ML conferences
Expert-level knowledge of SOTA in large auto-regressive transformer models, multi-modal encoders, and representation learning.
Experience with multimodal large language models (LLMs)
Strong programming skills in Python, maintaining ML code bases grounded in software engineering principles.
Preferred Qualifications
PhD in Machine Learning
Proven track record of deploying innovative ML technologies in production.
Familiarity with developing ML for resource-constrained devices.
Experience working with large cross-functional and diverse teams.
Pay & Benefits — Cupertino, California, United States
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 $184,700 and $324,800, 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.
Application Deadline
Apple accepts applications to this posting on an ongoing basis.
About the company
Apple
Large Enterprise
Apple Inc. is a global technology company known for its innovative products and services, including the iPhone, iPad, Mac computers, and Apple Watch. Founded in 1976, Apple has continuously pushed the boundaries of design and functionality, earning a reputation for high-quality consumer electronics and software solutions like iOS and macOS. With a strong commitment to user experience and privacy, Apple also leads in digital services, offering platforms such as the App Store, Apple Music, and iCloud. The company's focus on sustainability and corporate responsibility further enhances its standing as a leader in the technology sector.