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AIML-Machine Learning Engineer, Measurement

AIML-Machine Learning Engineer, Measurement Cupertino,California,United States Machine Learning and AI Imagine what you could do here. At Apple, new ideas have a way of becoming great products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. Apple delivers great features and great privacy to our users. The Privacy Preserving Machine Learning team works with teams all across the company to provide tools and support for state of the art privacy-preserving measurement and machine learning. We are looking for an outstanding candidate to become a member of the Privacy Preserving Machine Learning team. Description Collaborate with other engineers to design and develop end to end measurement systems with high utility that meet Apple’s industry-leading privacy bar. Operate independently to solve complex problems at the intersection of privacy-preserving measurement and machine learning. Contribute to the development of data collection systems that enable training and evaluation of generative AI systems while preserving user privacy. Successful candidates will need to have a strong technical background and interest or experience with deploying privacy-preserving systems. Strong interpersonal skills and the ability to influence and build consensus are crucial to success in this role. You will be working across a range of technologies, so adaptability to new problems and systems is a core skill. Minimum Qualifications 2 years of industry experience with a Bachelor’s degree or equivalent experience in Computer Science or a related technical field. Strong hands-on experience in software engineering, with proficiency in one or more object-oriented programming languages such as Python, Java, C++ and experience building highly scalable distributed systems. Experience with iOS development or Machine Learning including PyTorch and TensorFlow. Strong problem-solving skills, creativity in finding effective solutions, and the ability to work in a cross-functional team. BS in Computer Science, EE or equivalent experience Key Qualifications Preferred Qualifications Passion for customer privacy Experience with differential privacy or private federated learning Proven experience in deploying machine learning models into production environments. 5 years of industry experience Experience handling large-scale datasets and data-driven applications. Master's degree or PhD or equivalent experience in Computer Science, Software Engineering, or a related technical field. Education & Experience 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 $143,100 and $264,200, 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.Learn more about your EEO rights as an applicant. (https://www.eeoc.gov/sites/default/files/2023-06/22-088_EEOC_KnowYourRights6.12ScreenRdr.pdf) Apple Footer 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. Reasonable Accommodation and Drug Free Workplace policy Learn more (Opens in a new window) . Apple is a drug-free workplace. Reasonable Accommodation and Drug Free Workplace policy Learn more (Opens in a new window) .
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What You Should Know About AIML-Machine Learning Engineer, Measurement, Apple

At Apple, we’re on the hunt for a passionate AIML-Machine Learning Engineer focused on Measurement to join our innovative team in Monte Vista, CA. Imagine using your skills to design measurement systems that prioritize user privacy while ensuring high utility. As part of the Privacy Preserving Machine Learning team, you’ll collaborate with brilliant minds across the company to develop tools that enable groundbreaking AI systems, all while adhering to Apple’s top-notch privacy standards. In this role, you’ll find yourself solving complex challenges where machine learning intersects with privacy-preserving techniques. Your expertise in languages like Python, Java, or C++, and familiarity with machine learning frameworks such as PyTorch or TensorFlow will be key as you help build large-scale distributed systems. Here, we value creativity and problem-solving skills, so be prepared to think outside the box and provide effective solutions. If you have a strong background in software engineering, a passion for customer privacy, and a knack for working collaboratively in cross-functional teams, Apple could be your ideal workplace. Whether you’re just starting your career or are looking to elevate your experience, we offer a supportive environment where your contributions can directly impact users worldwide. Join us and help shape the future of AI in a privacy-conscious world!

Frequently Asked Questions (FAQs) for AIML-Machine Learning Engineer, Measurement Role at Apple
What are the responsibilities of the AIML-Machine Learning Engineer at Apple?

As an AIML-Machine Learning Engineer at Apple, you’ll be responsible for designing and developing end-to-end measurement systems that prioritize user privacy. Collaborating with engineers across various teams, you’ll tackle complex problems at the intersection of privacy-preserving measurement and machine learning, contributing to data collection systems that facilitate AI training while safeguarding user information.

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What qualifications are needed for the AIML-Machine Learning Engineer position at Apple?

To apply for the AIML-Machine Learning Engineer role at Apple, candidates should have a minimum of 2 years of industry experience and a Bachelor's degree in Computer Science or a related field. Key qualifications include strong software engineering skills, proficiency in object-oriented programming languages such as Python, Java, or C++, and experience with machine learning libraries like TensorFlow and PyTorch.

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What skills are preferred for the AIML-Machine Learning Engineer role at Apple?

Preferred skills for the AIML-Machine Learning Engineer position at Apple include a deep passion for customer privacy, experience with differential privacy or private federated learning, and proven expertise in deploying machine learning models in production environments. Candidates with a Master's degree or PhD are also encouraged to apply, particularly those with experience in handling large-scale datasets.

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How does Apple support employee growth for an AIML-Machine Learning Engineer?

Apple places a strong emphasis on employee development and growth. As an AIML-Machine Learning Engineer, you’ll have access to educational reimbursements, including tuition assistance for formal education. Additionally, Apple encourages participation in various employee stock plans, offering financial incentives for personal and professional growth.

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What does the work environment look like for an AIML-Machine Learning Engineer at Apple?

At Apple, the work environment fosters collaboration and innovation. AIML-Machine Learning Engineers engage in cross-functional teamwork, where adaptability to new problems and technologies is key. The culture encourages creative problem-solving and supports employees in making impactful contributions to cutting-edge projects.

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Common Interview Questions for AIML-Machine Learning Engineer, Measurement
Can you explain your experience with privacy-preserving machine learning?

When answering this question, detail any specific projects or systems you've worked on that involved privacy preservation. Highlight tools or methodologies you used, such as differential privacy techniques, and showcase your understanding of the impact of privacy on user data.

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What programming languages are you most comfortable with and why?

Discuss your proficiency in key programming languages relevant to the AIML role, like Python and C++. Provide examples of projects where you utilized these languages, and mention how you adapt your coding skills to different technical environments.

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Describe a challenging problem you faced in your previous role and how you resolved it.

Use the STAR method (Situation, Task, Action, Result) to structure your response. Focus on a specific challenge related to machine learning or system design and explain the steps you took to come up with a solution, emphasizing your problem-solving skills.

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How do you ensure the scalability of a machine learning model?

Talk about strategies you employed in previous projects to ensure scalability. This can include discussing architecture choices, data management techniques, or the use of cloud resources. Providing quantitative impact can strengthen your answer.

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What experience do you have with distributed systems?

Outline your hands-on experience with distributed systems, mentioning the technologies you’ve used, such as Apache Spark or Kubernetes. Highlight any projects that illustrate your capability in designing systems that can handle large data volumes efficiently.

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How do you stay updated with the latest trends in machine learning?

Share methods you use to stay informed, such as attending conferences, following influential AI researchers, or participating in online courses. Discuss how continuously learning helps you enhance your work and contributes to innovative solutions.

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Can you talk about an experience with software deployment?

Discuss a particular instance where you took a machine learning model from development to production. Highlight the tools you used for continuous integration and deployment, as well as the challenges faced during the process and how you overcame them.

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Describe how you approach teamwork and collaboration.

Emphasize your interpersonal skills and your ability to build consensus among cross-functional teams. Provide specific examples of how you collaborated with others to achieve shared goals, pointing out any challenges and how you navigated them.

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What do you understand by differential privacy?

Explain the concept of differential privacy in a clear and concise manner. It's crucial to touch on its importance in the context of user data protection and how it applies to machine learning systems you’ve worked on, indicating your familiarity with the concept.

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Why do you want to work at Apple as an AIML-Machine Learning Engineer?

Express your admiration for Apple's commitment to innovation and privacy. Share how your personal values align with Apple’s mission and how you believe your skills can contribute to their vision, detailing any specific aspects of the role that excite you.

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CULTURE VALUES
Inclusive & Diverse
Diversity of Opinions
Work/Life Harmony
Dare to be Different
Reward & Recognition
Empathetic
Take Risks
Growth & Learning
Transparent & Candid
Mission Driven
Passion for Exploration
Feedback Forward
BENEFITS & PERKS
Medical Insurance
Dental Insurance
Vision Insurance
Mental Health Resources
Life insurance
Disability Insurance
Health Savings Account (HSA)
Flexible Spending Account (FSA)
Learning & Development
Paid Time-Off
Maternity Leave
Social Gatherings
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EMPLOYMENT TYPE
Full-time, on-site
DATE POSTED
December 3, 2024

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