Machine Learning Engineer - Advertising Supply Forecasting

3 Months ago • All levels

Research Development

Job Description

At Apple, we focus deeply on our customers’ experience, and Apple Ads brings this approach to advertising, helping people find what they are looking for and advertisers grow their businesses. Our technology powers ads and sponsorships across Apple Services, including the App Store, Apple News, and MLS Season Pass. Everything we do is designed for trust, connection, and impact: respecting user privacy, integrating advertising thoughtfully, and delivering value for advertisers of all sizes. The role requires experience in predictive modeling, optimization, industrial engineering, demand forecasting, and time-series forecasting. The ideal candidate will have experience deploying data science and machine learning models with large datasets in an industry setting. Deep understanding and ability to compare predictive models, interpret and explain model results to stakeholders are also a plus. Candidates will also have experience working closely with data engineers to build efficient, scalable solutions.

Good To Have:

Masters' degree, Ph.D., or equivalent in a quantitative field
Experience in digital advertising or demand forecasting
Willingness to learn technical skills and domain knowledge
Familiarity with numpy, pandas, scikit-learn, prophet
Familiarity with job orchestration frameworks (git, Airflow, CI/CD, Kubernetes, Docker, Jenkins)
Experience with deep learning, LLMs, and Natural Language Processing

Must Have:

Bachelor's or equivalent experience in computer science, mathematics, or a quantitative field
Proficiency in Python and SQL
Comfort with cloud technologies (AWS, Snowflake)
Experience with Big Data tools (Hadoop, Spark, PySpark)
Experience in quantitative analysis (regression, classification, optimization, time-series)
Ability to communicate analysis results effectively to stakeholders
Ability to partner with engineering and develop model prototypes
Experience with end-to-end model implementation and production

Add these skills to join the top 1% applicants for this job

communication

data-analytics

forecasting-budgeting

github

game-texts

prototyping

aws

hadoop

spark

data-science

numpy

scikit-learn

deep-learning

pandas

ci-cd

docker

kubernetes

git

python

sql

jenkins

machine-learning

At Apple, we focus deeply on our customers’ experience. Apple Ads brings this same approach to advertising, helping people find exactly what they’re looking for and helping advertisers grow their businesses! Our technology powers ads and sponsorships across Apple Services, including the App Store, Apple News, and MLS Season Pass. Everything we do is designed for trust, connection, and impact: We respect user privacy, integrate advertising thoughtfully into the experience, and deliver value for advertisers of all sizes—from small app developers to big, global brands. Because when advertising is done right, it benefits everyone!

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The role requires experience in areas such as predictive modeling (classification and regression), optimization, industrial engineering, demand forecasting, and time-series forecasting. The ideal candidate will have working experience in deploying data science and machine learning models with large datasets in an industry setting. Deep understanding and ability to compare predictive models, evaluate their strengths and weaknesses in a particular context, and interpret and explain model results to a broad group of technical and non-technical stakeholders are also a plus. Driven candidates will also have experience working closely with data engineers to build efficient, scalable solutions. We are looking for a thoughtful and creative data scientist to join a team that creatively adapts state-of-the art analytical techniques to real-world business problems with an approach focused on rapid development, evaluation, and iterative improvement. Continuous learning is part of the job, both as it relates to technical skills and within the content and format of advertising domains (e.g. Apple News, Major League Soccer).

Bachelor's or equivalent experience in computer science, mathematics, or another quantitative field
Command over Python and SQL.
Comfort with cloud technologies such as AWS and Snowflake.
Experience with Big Data tools such as Hadoop, Spark and PySpark.
Experience in quantitative analysis including regression, classification, linear optimization, supply chain analytics, and time-series analyses.
Ability to communicate the results of analyses in a clear and effective manner with product and leadership teams to influence the overall strategy of the product.
Ability to partner with engineering, meet the data needs of the business, find creative analytical solutions, and develop initial prototypes to address business problems.
Experience with end-to-end implementation of a model prototype specifically training, processing, feature engineering, evaluating model outputs, and putting models into production.

Masters' degree, Ph.D. or equivalent experience in a quantitative field.
Experience in the digital advertising industry or a related field and/or experience with demand forecasting
Willingness to learn, both technically and in the domain of the data.
Familiarity with packages like numpy, pandas, scikit-learn, and prophet
Familiarity with job orchestration frameworks like git, Airflow, CI/CD, Kubernetes, Docker, Jenkins.
Experience and/or interest in deep learning, LLMs, and Natural Language Processing.

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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