SponsoredWW CSO - Machine Learning Engineer, Data Modeling
2025-08-28, Apple Inc.
Cupertino, California
WW CSO - Machine Learning Engineer, Data Modeling
WW CSO - Machine Learning Engineer, Data Modeling
**Cupertino, California, United States**
**Machine Learning and AI**
**Summary**
Posted: **Aug 26, 2025**
Weekly Hours: **40**
Role Number: **200613604-0836**
Imagine what you could do here. The people here at Apple don’t just create products — they create the kind of wonders that has revolutionized entire industries. It’s the diversity of those people and their ideas that inspires the innovation that runs through everything we do, from amazing technology to industry-leading environmental efforts. Join Apple, and help us lead the future generation of innovation.
We are looking for an outstanding Senior Machine Learning Engineer to develop advanced predictive modeling that drive actionable business decisions and build AI-driven personalization systems to enhance user experiences. You will use innovative ML techniques, Generative AI, and Causal Inference Models to develop AI-driven personalization and predictive models that extract meaningful insights from large-scale customer, market, and sales data. In this role, you will collaborate with a multidisciplinary team of ML engineers, data scientists, software engineers, researchers, designers and business partners to design, build, and deploy high-impact models. You will work on forecasting trends, optimizing business strategies, and developing AI-driven personalization that set new industry standards. This position provides a unique opportunity to work on real-world challenges at scale, influence critical business decisions, and innovate in the fields of predictive analytics, AI-driven personalization systems, and generative AI.
**Description**
In this role, you will focus on the following key areas:
- deploy predictive models to generate actionable insights for business strategy and decision-making.
- Develop AI-driven personalization that provide tailored suggestions based on customer behavior, preferences, and historical data.
- Leverage user segmentation and clustering to enhance personalization precision for different customer groups.
- Experiment with multi-modal data (text, images, customer interactions) to improve personalization.
- Implement hybrid personalization models (Collaborative Filtering, Content-Based, Knowledge Graphs) to optimize user experiences.
- Build real-time personalization pipelines that can dynamically adjust based on live user interactions.
- Lead the exploration for predictive modeling of Large Language Models and Generative AI, Causal Inference Model, GNN, venturing into new areas within these fields.
- Turn prototypes into automated pipelines and deploying them to production; deciding when to use out-of-the-box solutions vs. building custom solutions or a hybrid approach.
- Analyze and preprocess large scale datasets to extract meaningful patterns and ensure model accuracy
- Ongoing data analysis to build new or fine-tune existing models to optimize results
- Partner closely with software engineers to implement these models into high-performing systems and models in our production environment that can be applied to create amazing experience for our worldwide audience
- Actively engaging in all aspects of model development, from ideation, experimentation, triaging to deployment.
- Communicate results/reports with partners
- Maintain expertise in the latest advancements in AI technology. Partnering with your team members to prepare presentations, papers, and patents for your inventions
**Minimum Qualifications**
+ 5+ years of professional experience in building and deploying predictive models and AI-driven personalization at scale.
+ Proven expertise in data preprocessing, feature engineering, and analyzing large datasets to extract meaningful patterns.
+ Strong knowledge of innovative ML algorithms, including Generative AI, Multi-modal LLMs.
+ Solid understanding of insight modeling (Causal Inference Model, GNN, Generative AI, Forecasting).
+ Hands-on experience in forecasting models, anomaly detection, and AI-driven personalization (matrix factorization, contextual recommendation, collaborative filtering)
+ Proficiency in Python and key ML frameworks (TensorFlow, PyTorch, Keras, scikit-learn).
+ Experience working with Big Data tools (SQL, Spark, Hadoop) and cloud-based ML pipelines.
+ Track record of deploying ML models into production and optimizing for performance and scalability.
+ Ph.D. in Computer Science, Artificial Intelligence, Machine Learning or related field; or M.S. in related field with 3+ years experience applying machine learning engineer to real business problems
**Preferred Qualifications**
+ Excellent communication and soft skills.
+ Strong portfolio of shipped ML products, patents, or published research is a plus.
**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 $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. (https://www.apple.com/careers/us/benefits.html)
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.
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 (https://www.eeoc.gov/sites/default/files/2023-06/22-088\_EEOC\_KnowYourRights6.12ScreenRdr.pdf) .
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 (https://www.eeoc.gov/sites/default/files/2023-06/22-088\_EEOC\_KnowYourRights6.12ScreenRdr.pdf) .
Apple will not discriminate or retaliate against applicants who inquire about, disclose, or discuss their compensation.
Apple participates in the E-Verify program in certain locations as required by law.Learn more about the E-Verify program (https://www.apple.com/jobs/pdf/EverifyPosterEnglish.pdf) .
Apple is committed to working with and providing reasonable accommodation to applicants with physical and mental disabilities. Reasonable Accommodation and Drug Free Workplace policy Learn more .
Apple is a drug-free workplace. Reasonable Accommodation and Drug Free Workplace policy Learn more .
Apple will consider for employment all qualified applicants with criminal histories in a manner consistent with applicable law. If you’re applying for a position in San Francisco, review the San Francisco Fair Chance Ordinance guidelines applicable in your area.
It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.
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