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Machine Learning Algorithm Validation Engineer

Apple

Machine Learning Algorithm Validation Engineer

Apple

Sunnyvale, CA

·

On-site

·

Full-time

·

2w ago

Compensation

$147,400 - $272,100

Benefits & Perks

Healthcare

401(k)

Equity

Learning Budget

Healthcare

401k

Equity

Learning

Required Skills

Python

Machine learning

Computer vision

Statistical analysis

We are the Product Systems Quality team, and we are looking for a highly motivated and experienced Algorithm Validation Engineer with a passion for delivering robust, inclusive, and state-of-the-art Computer Vision and Machine Learning algorithms in Apple's next generation of products. You'll enjoy working on a team of quality engineers with diverse backgrounds as we refine the model pipelines that power Apple's trademark simple and elegant user experience.
Come be a part of our team and use both creativity and technical expertise to bring experiences to life that our customers love!

Description:

We are seeking an experienced Machine Learning Validation Engineer to lead the design and implementation of evaluation pipelines for Apple's ML systems. This is a technical leadership role for someone who bridges algorithm research, systems engineering, and customer experience. You'll be solving complex problems at the intersection of model performance, real-world constraints, and user impact.

Your work will require close partnership with algorithm development teams to design and execute live test procedures, aggressor searches, user studies, and annotation pipelines to improve and influence algorithm performance and design. You'll use data science techniques to design experiments that expose vulnerabilities in the models and investigate patterns of failure. By focusing on end-to-end system performance, you'll evaluate and represent the true customer experience while using a deep understanding of the various components within the models to test comprehensively and efficiently. You'll also work with hardware and software engineering teams to consider the system design and external factors that influence model performance.

You'll be working through every step of the product development cycle and will help make Apple products more reliable, flexible, and easy to use.

Preferred Qualifications:

Master's or PhD in Machine Learning, Computer Vision, Statistics, or related field

5 or more years of ML industry experience, including time spent debugging or improving deployed models

Strong background in statistical experimental design and hypothesis testing

Hands-on experience with Py Torch, Tensor Flow, or JAX-including model analysis and interpretability tools

Data analysis, visualization, and reporting experience with tools such as Tableau or Superset

Understanding of how to test and quantify performance of sensing technologies such as camera, IMU, capacitive, environmental, light, motion, radar, optical, acoustic, and evaluate user impact and performance

Minimum Qualifications:

Bachelor's degree or equivalent in Computer Science, Machine Learning, Electrical Engineering, Statistics, or related field

A minimum of 3 years of hands-on industry experience developing or validating ML/AI systems

Strong programming skills and hands-on experience with Python

Experience in testing products utilizing computer vision, computational photography, generative AI, machine learning, or related areas

Ability to communicate effectively and collaborate with partner teams

Committed to encouraging an open and inclusive work environment

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 $147,400 and $272,100, 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