Jobs

AIML - Senior ML Researcher in Foundation Models, Responsible AI
Cupertino, CA
·
On-site
·
Full-time
·
5d ago
Join us as we build world-class groundbreaking products for our customers! Apple's Responsible AI and Safety team is looking to hire a technical lead with a strong track record in Applied Research who is passionate about ML and foundation models with a focus on responsibility, fairness, and safety. In this role, you will lead the research and application of ML methods for technologies that power breakthrough user experiences while upholding Apple's values, privacy, and quality standards.
Description:
This role will be highly multifunctional. You will collaborate closely with top machine learning researchers and engineers, software engineers, and design teams to develop and deliver groundbreaking solutions for Apple products. We believe that the most exciting problems in machine learning research arise at the intersection of emerging technologies and real-world use cases. This is also where the most critical breakthroughs come from. As a researcher, you will:
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Define and deliver responsible machine learning technologies
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Develop methods and frameworks to train and evaluate foundation models with responsibility and safety in mind
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Research and advance safety alignment and model robustness methods for foundation models
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Research and develop mitigations and safeguards to ensure safe deployment of LLM's in Apple products
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Advocate for scientific and engineering excellence by contributing to the architecture and high-level structure of Apple's AI-powered platform and features
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Work multi-functionally on a diverse set of challenging problems and collaborate with extraordinary software engineers, machine learning engineers, and researchers to impact the future of Apple products
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Work closely with product and partner teams to drive requirement definition, technical quality of deliverables, and execution
Preferred Qualifications:
Experience with LLM training and safety alignment
BS, MS in Computer Science, Machine Learning, or related fields or an equivalent qualification acquired through other avenues
Minimum Qualifications:
4+ Years research or product deployment record in areas related to responsible AI, with publications in top ML venues (e.g., ACL, CHI, CVPR, EMNLP, FAccT, ICML, Interspeech, NeurIPS, UIST, etc.)
PhD in Computer Science, Machine Learning, or related fields or an equivalent qualification acquired through other avenues
Strong research fundamentals, machine learning principles, and development methodologies around LLMs, foundation models, and diffusion models
Proficient programming skills in Python and deep learning toolkits (e.g. JAX, Py Torch, Tensorflow)
Work with highly-sensitive content with exposure to offensive and controversial content
Strong organizational and operational skills working with large, multi-functional, and diverse teams
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 .
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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
L2
L3
L4
L5
L6
L2 · Business Analyst L2
0 reports
$114,215
total / year
Base
$45,686
Stock
$57,108
Bonus
$11,422
$79,951
$148,480
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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