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AIML - Senior Machine Learning Engineer - Data Science, Responsible AI and Safety
Cupertino, CA
·
On-site
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Full-time
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2d ago
Would you like to play a part in building the next generation of generative AI applications at Apple? We're looking for Machine Learning Engineers to work on ambitious projects that will impact the future of Apple, our products, and the broader world. This role is directed at assessing, quantifying, and improving the safety and inclusivity of Apple's Generative-AI powered features and products. In this role you'll have the opportunity to tackle innovative problems in machine learning, particularly focused on large language models for text generation, diffusion models for image generation, and mixed model systems for multimodal applications. As a member of Apple's Responsible AI group you will be working on a wide array of new features and research in the generative AI space. Our team is currently interested in large generative models for vision and language, with particular interest on Responsible AI, safety, fairness, robustness, explainability, and uncertainty in models.
Description
This role focuses on developing, carrying-out, interpreting, and communicating pre- and post-ship evaluations of the safety of Apple Intelligence features. Both human grading and model-based auto-grading are thoughtfully leveraged to power these evaluations. Additionally, this role researches and develops auto-grading methodology & infrastructure to benefit ongoing and future Apple Intelligence safety evaluations.
Producing safety evaluations that uphold Apple's Responsible AI values requires thoughtful data sampling, creation, and curation for evaluation datasets; high quality, detailed annotations and careful auto-grading to assess feature performance; and mindful analysis to understand what the evaluation means for the user experience.
This role heavily draws on applied data science, scientific investigation and interpretation, cross-functional communication and collaboration, and metrics reporting and presentation.","responsibilities":"Develop metrics for evaluation of safety and fairness risks inherent to generative AI features.
Design datasets, identify data needs, and work on creative solutions, scaling and expanding data coverage through human and synthetic generation methods.
Develop auto-grading technologies and approaches for application in safety evaluations of generative AI features.
Provide technical direction and expertise to team-wide initiatives in safety auto-grading.
Use and implement data pipelines, and collaborate cross-functionally to execute end-to-end safety evaluations.
Work with highly-sensitive content with exposure to offensive and controversial content.
Preferred Qualifications
Experience working in the Responsible AI space.
Prior scientific research and publication experience.
Strong organizational and operational skills working with large, multi-functional, and diverse teams.
Curiosity about fairness and bias in generative AI systems, and a strong desire to help make the technology more equitable.
Minimum Qualifications
MS, or PhD in Computer Science, Machine Learning, Statistics, or related fields; or an equivalent qualification acquired through other avenues.
Experience working with generative models for evaluation and/or product development, and up-to-date knowledge of common challenges and failures.
Strong engineering skills and experience in writing production-quality code in Python.
Deep experience in foundation model-based AI programming (i.e.: using DSPy for optimizing foundation model prompts, for example) and a drive to innovate in this space.
Experience working with noisy, crowd-based data labels and human evaluations.
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 .
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 $181,100 and $318,400, 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.
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Appleについて

Apple
PublicApple Inc. is an American multinational technology company headquartered in Cupertino, California, in Silicon Valley, best known for its consumer electronics, software and online services.
10,001+
従業員数
Cupertino
本社所在地
$3.5T
企業価値
レビュー
3.9
10件のレビュー
ワークライフバランス
2.5
報酬
4.2
企業文化
3.8
キャリア
3.5
経営陣
3.2
72%
友人に勧める
良い点
Great benefits and compensation
Talented colleagues and supportive teams
Learning opportunities and mentorship
改善点
Work-life balance challenges
High stress and pressure
Fast-paced environment
給与レンジ
11,365件のデータ
Junior/L3
L2
L3
L4
L5
L6
M3
M4
M5
M6
Principal/L7
Senior/L5
Staff/L6
Junior/L3 · Data Scientist ICT2
0件のレポート
$121,979
年収総額
基本給
-
ストック
-
ボーナス
-
$103,682
$140,276
面接体験
3件の面接
難易度
3.3
/ 5
期間
28-42週間
内定率
33%
体験
ポジティブ 33%
普通 0%
ネガティブ 67%
面接プロセス
1
Application Review
2
Recruiter Screen
3
Technical Phone Screen
4
Onsite/Virtual Interviews
5
Team Matching
6
Offer
よくある質問
Coding/Algorithm
System Design
Behavioral/STAR
Technical Knowledge
Past Experience
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