This role pays more than
69%
of similar roles. Most pay
$212,673–$266,050
— the shaded band above.
At the midpoint, this role pays about
$255k
versus about
$239k
for comparable roles.
Based on 240 similar postings.
Employer
About Apple Inc
Apple Inc. is a multinational technology company known for designing and manufacturing consumer electronics, software, and online services, including the iPhone, Mac, iPad, and App Store. Industry: Consumer Electronics & Software
Apple Inc currently has
1984 open roles
on FindRole.
Listed pay typically runs
$175,000–$277,600
across 1590 roles with salary data.
Senior Machine Learning Scientist - Ad Campaign Optimization joins the team responsible for building next-generation ad platforms and ensuring high-quality experiences across various services. This role involves designing and building scalable solutions for budget and bid optimization, as well as developing production code to generate high-quality ad recommendations. The candidate will lead the development of advanced techniques and algorithms to improve the ad network while performing large-scale experiments to understand their effects. Key technical requirements include proficiency in Java or Python, experience with Spark, Hadoop, or other distributed frameworks, and expertise in machine learning, quantitative methods, control systems, or reinforcement learning. The role focuses on solving complex problems in ads optimization, recommendations, and search relevance within a fast-growing business environment to improve performance for advertisers and users alike.
Develop and implement machine learning models and production code to generate high-quality ad recommendations.
Design and build scalable solutions for budget and bid optimization to improve advertiser performance.
Lead the development of advanced algorithms and techniques to enhance the ad network's capabilities.
Conduct large-scale, complex experiments to measure the impact of new features and systems.
Create a technical innovation roadmap by analyzing ad network behavior and business requirements.
Translate research concepts into production-quality code for high-scale advertising platforms.
Formulate and advocate for R&D objectives and results to executive leadership and product management.
What we're looking for
5+ years of experience building machine learning and quantitative optimization capabilities at scale.
Experience in machine learning, quantitative methods, control systems, or reinforcement learning.
Ability to implement research concepts into production quality code.
Experience defining clear, testable research hypotheses with intended business impact.
Deep knowledge of design of experiments and online experimentation approaches.
Ability to advocate for R&D objectives to cross-functional teams and executive leadership.
Experience contributing to or reviewing research for top conferences and publications.
Deep fluency in Java or Python and experience with Spark, Hadoop, or other distributed frameworks.
Master's degree in Machine Learning, Statistics, Control Theory, Forecasting, Optimization, Reinforcement Learning, or a related field (or equivalent industry experience).
Experience in ads optimization, recommendations, or search relevance optimization (preferred).
PhD in Machine Learning, Statistics, Control Theory, Forecasting, Optimization, Reinforcement Learning, or a related field (preferred).