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AIML - Staff ML Engineer, Responsible AI

Apple

AIML - Staff ML Engineer, Responsible AI

Apple

Cupertino, CA

·

On-site

·

Full-time

·

5d ago

Join Us in Shaping the Future of Generative AI at Apple! Are you passionate about making AI systems safer, more inclusive, and globally representative? Apple is seeking an expert Machine Learning Engineer to shape the future of responsible AI for the next generation of generative features. In this role, you will lead the responsible AI lifecycle end-to-end: assessing risks, defining policies, developing mitigation strategies, and driving continuous improvements. Your work will directly influence how we evaluate, align, and monitor the safety of large language and multimodal models. As part of Apple's Responsible AI group within the Human-Centered Machine Intelligence (HCMI) organization, you'll collaborate with cross-functional partners to minimize unintended consequences across people, systems, and society while elevating feature capabilities and the overall user experience. Together, we'll anticipate challenges, measure real-world impact, and deliver trusted, high-quality AI experiences to users around the globe. You'll also contribute to forward-looking research in fairness, robustness, uncertainty, and safety - pushing the boundaries of responsible AI at scale.

Description:

Our team leads Responsible AI initiatives for global generative AI products, operating at the intersection of policy, product, and GenAI. We're seeking candidates who will shape safety policies in partnership with leadership, design, engineering, legal, and regulatory stakeholders-ensuring our safeguards advance both user protection and product innovation.

These individuals will work on architecture mitigation and safety alignment strategies for generative models, drive integration in production. Additionally, they will work on developing models, tools, datasets, and evaluation methods to monitor, diagnose failures, and improve the safety of generative models throughout the deployment lifecycle. We do all these by incorporating human and automated feedback, post-launch to continuously improve feature safety and user trust.

Preferred Qualifications:

BS, MS, or PhD in Computer Science, Machine Learning, or related field, or equivalent experience

Proven success contributing in a highly cross-functional environment

Experience shipping complex AI systems at global scale

Background in model explainability, uncertainty estimation, or interpretability

Curiosity and research interest in fairness, bias, and the societal impacts of generative AI

Passion for building innovative, high-impact products that draw upon interdisciplinary skills

Minimum Qualifications:

3+ years of proven ability in machine learning, including work with generative models (Transformers, LLMs, VLMs), NLP, or Computer Vision

Proficiency in Python and data science libraries (e.g. Pandas) with strong skills in data analysis, visualization, and applied ML workflows

Excellent interpersonal skills and proven ability to translate sophisticated technical insights for cross-functional partners, senior leadership, and executives

Strong analytical and independent problem-solving skills, with ability to navigate ambiguity

Experience designing and supporting human and automated evaluations, particularly with complex, nuanced, or multi-labeled data

Hands-on experience collecting and analyzing language, vision, or multimodal datasets

Background in failure analysis, quality engineering, or robustness testing for ML-driven systems

Must be comfortable working with sensitive or potentially offensive content

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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About Apple

Apple

Apple

Public

A 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