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Apple Senior Machine Learning Engineer - Large Language Models & Generative AI in Cupertino, California

Senior Machine Learning Engineer - Large Language Models & Generative AI

Santa Clara Valley (Cupertino),California,United States

Machine Learning and AI

The Intelligence Platform team empowers clients across Apple’s operating systems with high quality user-centric knowledge and inferences that enable next generation user experiences. We’re an applied Machine Learning team that leverages state of the art technologies like generative AI, graph machine learning, and private learning to deliver high quality inferences. We are in search of an accomplished and driven Senior Machine Learning Engineer who has a robust understanding of Large Language Models and Generative AI. Your primary role will involve decoding and applying groundbreaking research and setting the course for the team in this thriving field. By contributing to our team, you'll play an integral part in developing Siri, Photos, Music, and various other services, leaving a significant footprint on the evolution of our AI platforms. Join us in our exciting journey as we push the frontiers of Machine Learning and Generative AI. Your expertise and contributions will be invaluable in shaping the future of our Intelligence Platform.

Key Qualifications

  • In-depth experience in Machine Learning, with a particular emphasis on Large Language Models (LLMs) and Generative AI.

  • Published research in the field of Machine Learning or AI is highly desirable, indicating an ability to not only understand but also contribute to cutting-edge research.

  • Proven ability to comprehend, interpret, and apply cutting-edge research into tangible applications.

  • Comprehensive knowledge and hands-on experience with fine-tuning approaches and training models.

  • Proven problem-solving and leadership abilities, with the capacity to steer the team's research and practical applications in a collaborative and fast-paced environment.

Description

As a Senior Machine Learning Engineer on the Relevance and Graph Inference Team, you’ll join a phenomenal team of hardworking engineers and researchers and will be entrusted with a range of responsibilities. Your tasks will include: - Leading the exploration and application of Large Language Models and Generative AI, venturing into new areas within these fields. - Translating the latest research into high-performing systems and models that can be practically applied to enhance user experiences. - Setting the team's strategic direction, cultivating an environment that encourages innovation and professional growth. - Actively engaging in all aspects of model development, from ideation and experimentation to deployment. - Collaborating with various teams to develop and implement Machine Learning solutions, ensuring performance optimization and alignment with broader business goals.

Education & Experience

An advanced degree (Master's or Ph.D.) in Computer Science, Artificial Intelligence, Machine Learning, or a related field is required Ongoing professional development in Machine Learning and Artificial Intelligence domains is expected.

Additional Requirements

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 $170,700.00 and $300,200.00, 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 (https://www.apple.com/careers/us/benefits.html) 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.

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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 (Opens in a new window) .

Apple will not discriminate or retaliate against applicants who inquire about,disclose,or discuss their compensation or that of other applicants. United States Department of Labor. Learn more (Opens in a new window) .

Apple will consider for employment all qualified applicants with criminal histories in a manner consistent with applicable law. If you’re applying for a position in San Francisco,review the San Francisco Fair Chance Ordinance guidelines (opens in a new window) applicable in your area.

Apple participates in the E-Verify program in certain locations as required by law. Learn more about the E-Verify program (Opens in a new window) .

Apple is committed to working with and providing reasonable accommodation to applicants with physical and mental disabilities. Apple is a drug-free workplace. Reasonable Accommodation and Drug Free Workplace policy Learn more (Opens in a new window) .

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