Summary Posted: Jun 14, 2024 Weekly Hours: 40 Role Number: 200555292 Play a part in building the next revolution of ML technology. Our team builds groundbreaking technology that will change the way we create machine learning solutions at Apple. The Machine Learning Research (MLR) team is looking for a passionate scientist to explore the next generation of machine learning introspection technologies with particular attention to fairness and bias in AI as well as generalization and robustness. As a member of MLR, you will work on some of most ambitious technical problems, collaborate with world-class ML Engineers and Researchers, develop new ML solutions that will alter future Apple products, and publish in top-tier international conferences. Description Description Are you interested in applying pioneering machine learning algorithms to extraordinary products? Are you passionate about advancing the state-of-the-art and pursuing phenomenal innovations?
You will help to identify gaps in the research field, define a research agenda, and develop innovative ML strategies for challenging problems. We'll provide technical mentorship and guidance, while you apply your passion and skills to create innovative solutions. You'll have the ability to work both independently and collaboratively with other researchers and product teams. You'll have the chance to see how we innovate on products and highly-visible features that are used by millions every day. You will be responsible for delivering ML technologies aligned with the core values of Apple - ensuring the highest standards of quality, scientific rigor, innovation, and respect for user privacy.
Minimum Qualifications Minimum Qualifications Demonstrated expertise in machine learning with a passion for understanding bias and fairness in AI Strong publication record in relevant conferences (e.g., NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, SIGGRAPH, KDD, ACL, FAccT) Good programming skills in Python Hands-on experience working with deep learning toolkits such as Tensorflow, PyTorch, or Keras Strong mathematical skills in linear algebra and statistics Ability to formulate a research problem, design, experiment and implement solutions Proven success in a collaborative environment Key Qualifications Key Qualifications Preferred Qualifications Preferred Qualifications PhD or equivalent experience in Computer Science, or related technical field is ideal Education & Experience Education & Experience Additional Requirements Additional Requirements Pay & Benefits 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 $138,900 and $208,300, 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. More 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.
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