101 jobs for "Applied Machine Learning Scientist"

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Research Scientist, Applied Machine Learning Security (Agent Systems), SEAR

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Sr. Director, Applied Researcher

At Capital One - McLean · San Francisco

Posted on Oct 16

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Multimodal AI Applied Scientist, SIML - ISE

At Apple - Cupertino

Posted on Oct 19

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Senior Engineering Manager, Agentic AI & Intelligent Reasoning

At Apple - Santa Clara

Posted on Oct 16

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AIML - Manager, Applied AI Science - LLM/VLM-as-judge

At Apple - Cupertino

Posted on Oct 14

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Senior Engineering Manager, Conversational AI & Knowledge Intelligence

At Apple - Santa Clara

Posted on Oct 11

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Senior Engineering Manager, Conversational AI & Knowledge Intelligence

At Apple - Santa Clara

Posted on Oct 11

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Applied Researcher 5 (AI Foundations: Evaluation and Agentic Workflows)

At Capital One - McLean · Cambridge

Posted on Nov 8

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Applied Researcher 5

At Capital One - San Jose · San Francisco

Posted on Nov 6

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Machine Learning Engineer, Search & Knowledge Quality

At Apple - Santa Clara

Posted on Oct 19

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Applied Data Solutions Program, Internships - Summer 2027

At Apple - Austin

Posted on Oct 17

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Machine Learning Engineer - Apple Store Online

At Apple - Bengaluru

Posted on Oct 16

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Apple

Multimodal AI Applied Scientist, SIML - ISE

Cupertino, CA$184,700 – $324,800Posted 20 days ago

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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.

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.

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.

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 $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.

About Apple

Working at Apple means doing more than you ever thought possible and having more impact than you ever imagined.

Size: 10,000+ employees
Industry: Technology: Manufacturing

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