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Apple

ML Data Operations Engineer

Cupertino, CA$175,000 – $308,500Posted 28 days ago

Apply on company site View full job

Why you should apply for a job to Apple:

Ranked as one of the Best Technology Companies in 2020
3.7/5 in overall job satisfaction
3.1/5 in supportive management
66% say women are treated fairly and equally to men
65% would recommend this company to other women
66% say the CEO supports gender diversity

Ratings are based on anonymous reviews by Fairygodboss members. See all reviews ›

Imagine what you could do here. At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. Dynamic, smart people and inspiring, innovative technologies are the norm here. The people who work here have reinvented entire industries with all Apple Hardware products. The same passion for innovation that goes into our products also applies to our practices, strengthening our commitment to leave the world better than we found it. Join us to help deliver the next groundbreaking Apple product.

Do you love working on challenges that no one has solved yet? As a member of our dynamic group, you will have the unique and rewarding opportunity to craft upcoming products that will delight and inspire millions of Apple's customers every single day.

Description

Apple's ML Data Operations group is seeking a Data Operations Engineer to support internal data collection efforts powering our next generation of consumer machine learning features. In this role, you will work shoulder-to-shoulder with full-time Apple scientists and engineers, not just coordinating logistics, but developing a genuine technical understanding of the ML experiments you support. You will be responsible for the hands-on bring-up, execution, and quality oversight of internal data collection studies, operating in a highly collaborative and technically demanding cross-functional environment","responsibilities":"Plan, execute, and track internal ML data collection studies in close collaboration with researchers, engineers, and scientists across the organization

Develop a working understanding of the ML experiments being supported, including model objectives, data requirements, labeling, and evaluation criteria, to ensure datasets quality

Bring up and maintain pre-release hardware and software platforms used for data collection, performing hands-on troubleshooting and triage to minimize study disruptions

Create and maintain clear technical documentation for hardware/software platform setup, study protocols, and data handling procedures

Manage day-to-day logistics of internal study sessions, including scheduling participants, configuring hardware and software setups, and maintaining smooth session flow

Collaborate with algorithm, infrastructure, and hardware/software teams to gather and validate data collection requirements before and during study execution

Track and communicate study progress, blockers, participant throughput, and dataset status to cross-functional partners and senior stakeholders

Identify gaps in existing workflows and take initiative to define, document, and socialize process improvements

Preferred Qualifications

10 years of experience in user research operations, data collection coordination, or a related technical operations role.

Hands-on familiarity with ML data pipelines, annotation tools, or dataset management practices.

Experience working directly with engineering and science teams, with comfort reading technical documentation, data schemas, or experiment specifications.

Familiarity with handling sensitive human data and adhering to strict privacy and consent protocols.

Highly organized self-starter who can manage multiple concurrent internal studies with minimal oversight.

Strong interpersonal and written communication skills, with the ability to collaborate fluidly across both technical and non-technical stakeholders.

Strong attention to detail with the ability to identify data anomalies and inconsistencies during live collection.

Minimum Qualifications

Bachelor's degree in HCI, Cognitive Science, Psychology, Engineering, Operations, or equivalent combination of education and relevant experience.

Experience supporting or executing human user studies, behavioral research, or data collection operations in an academic or industry setting.

Track record of partnering with ML engineers or researchers to define data requirements, quality standards, or collection specifications.

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 $175,000 and $308,500, 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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