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Machine Learning Engineer - Product Marketing Customer Analytics

Apple

Machine Learning Engineer - Product Marketing Customer Analytics

Apple

Cupertino, CA

·

On-site

·

Full-time

·

2w ago

Compensation

$212,000 - $318,400

Benefits & Perks

Healthcare

401(k)

Equity

Learning Budget

Relocation Assistance

Healthcare

401k

Equity

Learning

Required Skills

Machine Learning

Predictive Analytics

Python

Data Processing

SQL

At Apple, new ideas have a way of becoming excellent products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish! The Product Marketing Customer Analytics team is seeking a Machine Learning Engineer with deep technical experience in predictive analytics and analytic engineering.

Description:

Support Product Marketing, Investor Relations, and the Executive Team with predictive analytics for customer product and services engagement. Understand product requirements then translate them into modeling tasks and engineering tasks

Develop scalable ML algorithms and models to understand customer behavior and provide leadership with actionable insights and recommendations

Design and implement end-to-end machine learning pipelines-from feature engineering to model serving- using best in class MLOps frameworks

Develop and optimize deep learning and traditional ML solutions on high-volume datasets using GPU clusters or distributed CPU environments.

Experiment with cutting-edge algorithms, providing advanced insights into customer behavior and engagement.

Manage ML projects through all phases, including data quality, algorithm/feature development, predictive modeling, visualization, and deployment and maintenance.

Tackle difficult, non-routine analysis/prediction problems, applying advanced ML methods as needed.

Partner with peers to build and prototype analysis pipelines that provide insights at scale.

Collaborate with data engineers and infrastructure partners to implement robust solutions and operationalize models. Enhance and evolve solutions to meet changing business needs with agility.

Preferred Qualifications:

Excellent understanding of analytical methods and machine learning algorithms including regression, clustering, classification, optimization, and other advanced analytic techniques.

8+ years of proven experience building and scaling predictive models across distributed systems (eg: Spark, Kubernetes, GPU clusters), production model hosting, and handling end-to-end performance optimization to solve business problems.

8+ years of hands-on programming skills (Python, and/or Spark) for large-scale data processing, deriving key insights, developing machine learning models on structured and unstructured data, and with demonstrated success maintaining robust, high-throughput ML pipelines in a production environment.

Comfortable with advanced deep learning frameworks (Tensorflow, Py Torch) and adept at designing and scaling ML platforms that include feature stores, automated retraining pipelines and CI/CD integration. Able to design systems to handle high-volume ML workflows and implement scalable, fault-tolerant solutions.

Solid technical database and data modeling knowledge (Oracle, Hadoop, Snow Flake), and experience optimizing SQL queries on large dataset for performance-critical analytics.

Able to work effectively on ambiguous data and constructs within a fast-changing environment, tight deadlines and priority changes

Strong communication skills and ability to explain complex technical topics to both data science peers and non-technical business stakeholders, effectively presenting findings and recommendations to senior executives.

Demonstrated success in partnering cross-functionally, guiding diverse technical teams, aligning business stakeholders, invested in collective success of teams and project outcomes.

Minimum Qualifications:

8+ years of hands-on programming skills for large-scale data processing

Graduate degree required in Computer Science, Statistics, Data Mining, Machine Learning, Operations Research, or related field

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 $212,000 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