ML - Data Scientist

Apple Inc.; Sunnyvale (CA); Presencial; USD 185.000 - 325.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Medical and dental coverage

Retirement benefits

Stock awards programs

Tuition reimbursement

Descripción de la vacante

Apple Inc. is seeking an experienced evaluator to determine when a generative imaging feature is ready to ship. You will build measurement systems, golden sets, and annotation workflows, and automate metrics to produce trustworthy quality signals guiding model development and releases.

You will set the bar with partners across ML, engineering, and design, reporting model-vs-model comparisons with confidence and breakdowns by content type and failure mode.

Formación

• MS or higher with at least 5 years in industry.
• Experience designing and analyzing evaluations and experiments for ML quality.
• Strong Python and SQL; ability to build evaluation pipelines and small tools.
• Familiarity with AI-assisted analysis workflows and foundation models.

Responsabilidades

• Build the measurement foundation for generative imaging features.
• Create golden/evaluation sets and analyze data distributions.
• Develop automated metrics and Judge systems for model comparison.
• Collaborate with ML, engineering, and design to define quality standards.

Conocimientos

Python

SQL

Data science

ML evaluation

Statistical testing

Educación

Master's degree

Herramientas

Evaluation pipelines

Descripción del empleo

Do you want to decide whether a generative imaging feature is good enough to ship? Our team evaluates generative image and video features. These features reach a very large number of people on Apple devices. You will build the evaluation systems, human-annotation programs, and automated metrics that turn "this looks better" into measurable, trustworthy quality signals. Those signals guide model development and release decisions.

Description

Your findings determine which models ship.What you'll doBuild the measurement foundation. Design and maintain golden sets and evaluation sets, analyzing data distributions so results stay representative and known defects stay covered.Run human evaluation at quality. Write and iterate annotation guidelines and label schemas, build or adapt lightweight labeling tools for image and video review, monitor annotator quality, and resolve disagreements and guideline ambiguity.Automate the repeatable parts. Develop automated metrics and LLM-as-judge systems, calibrate them against human labels, and track where they diverge.Make the results decision-ready. Report model-vs-model comparisons with confidence intervals, significance testing, and breakdowns by hotspot, content type, and failure mode — then turn them into root-cause findings and prioritized recommendations.Set the bar with your partners. Work with ML, engineering, and design to define quality standards, and communicate results clearly to technical and non-technical audiences alike.

Minimum Qualifications

• MS and a minimum of 5 years relevant industry experience
• 5+ years of experience in data science, machine learning evaluation, algorithm analysis, or related technical disciplines.
• Experience designing and analyzing evaluations and experiments, especially for ML or generative model quality. This includes sampling design, significance testing, and confidence intervals.
• Strong Python skills and comfort with SQL, with the ability to build and maintain evaluation pipelines and small tools.
• Familiarity with AI-assisted analysis workflows, foundation models, agentic systems, or intelligent automation approaches for technical problem solving.

Preferred Qualifications

• Experience evaluating 3D Gaussian splats or diffusion models, or assessing perceptual quality.
• Experience building LLM or VLM judges and validating them against human ratings.
• Experience building web-based labeling or review tools.
• Ability to run several work-streams in parallel and prioritize them.
• Proven cross-functional collaboration and the ability to learn new tools quickly.
• Strong written and verbal communication, including explaining statistical tradeoffs to engineers and product partners.

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
• 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.

Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote 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

At Apple, we believe accessibility is a fundamental human right. You’ll find that idea reflected in everything here — in our culture, our benefits and our digital tools. By welcoming as many perspectives as possible, we help you build a career where you feel like you belong.

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Apple accepts applications to this posting on an ongoing basis.