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Benefits & Perks
•Flexible PTO policy
•Wellness benefits
•Learning and development stipend
•Remote work flexibility
Required Skills
TensorFlow
Airflow
SQL
AIML - Data Scientist, Evaluation
3 weeks ago• Cupertino, CA
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About Us
Working at Apple means doing more than you ever thought possible and having more impact than you ever imagined.
Size: 10000+ employees
Industry: Technology, Information Technology, Software, Consumer Goods & Services
Do you get excited by driving product impact via measurement and evaluation, for products and services used by hundreds of millions of people globally? The vision for the AIML Evaluation organization is to improve products by using data as the voice of our customers. Within this organization the mission of the Data Science and Insight team is to inform product evolution through measurement, evaluation, and analysis of the user experience. You will partner with Apple Intelligence engineering teams to improve product quality and guide feature development with data, to deliver amazing experiences across i Phone, i Pad, Home Pod, Mac, Apple Watch, Apple tv, across dozens of languages.
Description:
Research and develop evaluation methods to improve the quality of Apple Intelligence user facing products. Work with evaluation/experimentation engineering teams to get your methodological developments translated into technologies that Apple Intelligence engineering will use every day.
Work with large, complex data sets. Solve difficult, non-routine analysis problems, applying advanced analytical methods as needed. Conduct analysis that includes data gathering and requirements specification, processing, analysis, ongoing work, and presentations.
Build and prototype analysis pipelines iteratively to provide insights at scale. Develop comprehensive knowledge of Siri Search data structures and metrics, advocating for changes where needed for product development.
Partner closely with Apple Intelligence search engineering teams on core machine learning algorithms and systems that are part of product's ability to understand and respond to requests.
You should be passionate about building outstanding products. This position involves a wide variety of skills and innovation.
","responsibilities":"Design and Own End-to-End Evaluation Frameworks: Develop rigorous evaluation methodologies for AI/ML systems, including metric definition, sampling strategy, experiment design, and statistical validity checks. Build scalable pipelines that ensure trustworthy, reproducible, and interpretable results across product surfaces and model iterations.
Build High-Quality Evaluation Datasets & Human-in-the-Loop Systems: Create and maintain gold-standard datasets for offline and online model assessment. Lead data generation and annotation workflows (e.g., human ratings, Red Teaming, preference data, domain-specific evals), ensuring coverage, data quality, bias mitigation, and alignment with product and safety goals.
Partner Cross-Functionally to Drive Model & Product Decision-Making: Translate evaluation insights into actionable recommendations for model training, ranking, and product launches. Collaborate closely with Research, Engineering, Product, and Safety teams to define quality bars, monitor regressions, optimize user experience, and guide roadmap prioritization.
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Preferred Qualifications:
Applicants have a good understanding of large language model (LLMs), including their architecture, training methods, prompt engineering and fine-tuning for specific tasks.
Hands-on experience in applying LLMs to solve technical problems, such as data analysis, data automation, synthetic data generation, with proven ability to optimize model performance for accuracy and efficiency.
Ph.D. in machine learning, computer science, statistics, operations research or other quantitative fields.
5 years of relevant work experience.
Minimum Qualifications
Experience in data science, machine learning, and analytics, including statistical data analysis and A/B testing.
Experience articulating and translating business questions and using statistical techniques to arrive at an answer using available data.
Strong programming skills, including data-querying skills (SQL and/or Spark, etc.) and experience with a scripting language for data processing and development (e.g., Python, R, or Scala).
Excellent collaboration skills to achieve impactful results by working effectively with diverse cross-functional teams, including PMs, engineers, data scientists, and others.
B.S. in Machine Learning, Computer Science, Statistics, Operations Research or other quantitative fields.
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 .
Client-provided location(s): Cupertino, CA
Job ID: apple-200636357-3337_rxr-660
Employment Type: OTHER
Posted: 2026-01-07T19:13:49
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About Apple

Apple
PublicA technology company that designs, manufactures, and markets consumer electronics, personal computers, and software.
10,001+
Employees
Cupertino
Headquarters
$3.5T
Valuation
Reviews
4.0
10 reviews
Work Life Balance
4.0
Compensation
4.2
Culture
3.8
Career
3.5
Management
3.2
75%
Recommend to a Friend
Pros
Great coworkers and people
Excellent benefits and perks
Fast-paced and engaging work environment
Cons
High expectations and pressure
Management quality varies
Limited career progression opportunities
Salary Ranges
17,968 data points
Junior/L3
L2
L3
L4
L5
L6
M3
M4
M5
M6
Principal/L7
Senior/L5
Staff/L6
Junior/L3 · Data Scientist ICT2
0 reports
$121,979
total / year
Base
-
Stock
-
Bonus
-
$103,682
$140,276
Interview Experience
5 interviews
Difficulty
3.4
/ 5
Duration
28-42 weeks
Offer Rate
20%
Experience
Positive 20%
Neutral 40%
Negative 40%
Interview Process
1
Application Review
2
Recruiter Screen
3
Technical Phone Screen
4
Behavioral Interview
5
Onsite/Virtual Interviews
6
Team Matching
7
Offer
Common Questions
Coding/Algorithm
System Design
Behavioral/STAR
Technical Knowledge
Culture Fit
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