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Senior ML Engineer - Experimentation

1 week ago Cupertino, CA

At Apple, we work every day to create products that enrich people's lives. Our Advertising Platforms group makes it possible for people around the world to easily access informative and imaginative content on their devices while helping publishers and developers promote and monetize their work. Today, our technology and services power advertising in Search Ads in the App Store and Apple News. Our platforms are highly-performant, deployed at scale, and setting new standards for enabling effective advertising while protecting user privacy.

Ads ML Experimentation team is looking for a Senior Software Engineer to build the next generation of software platform and systems to advance experimentation that connect millions of global users to content from publishers and developers. Your work will drive the experimentation framework development of machine learned algorithm at scale. You will build sophisticated systems essential in the end-end development of predictive algorithms. You will design and engineer tools for managing AB test experiments, for performing exploratory analysis, and for real-time monitoring of experiment behavior, while preserving privacy of our customers.

Description

Partner with business leaders and stakeholders to design, implement and evolve the features of a multivariate experimentation platform. Promote experimentation best practices across the organization. Execute on the experimentation roadmap and future integrations with data-driven prioritization. Exercise strong judgment and make thoughtful decisions with ambiguous situations. Striking the right balance between short-term wins vs. long-term success based on various constraints.

You will join and contribute to a culture that emphasizes observability and understandability, reliability, resiliency, simplicity, reusability, extensibility, scalability, velocity and productivity. We are one team, nurturing each other's growth and supporting each other in delivering for our customers and Apple.

Preferred Qualifications

Degree in Computer Science, Statistics, Applied Math or related field.

5+ years of industry experience designing, building, maintaining, and extending web-scale production systems.

Exposure to AB testing and machine learning methodologies.

Minimum Qualifications

Skilled at designing and building complex large-scale and distributed software systems in cloud computing environments like AWS

Strong experience in Experimentation frameworks, A/B testing and Machine Learning methodologies

Fluency in programming languages like Java, Scala, Python and SQL

Experience with event stream processing (ESP) technologies like Spark Streaming, Kafka, Flink or equivalent

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Experience with backend object stores, automated data pipelines, cloud-native data storage and processing frameworks

Familiarity with data-oriented workflow orchestration frameworks like Airflow, Kubeflow, etc.

Familiarity with statistics and ability to use data analysis techniques to understand data quality, profile system loads, relationships between business metrics, and technical performance

Excellent communication, social and presentation skills

Skilled at operating in a cross-functional organization

Ability to condense complex concepts and analysis into clear and concise takeaways that drive action

Prior experience in advertising industry is a plus

Prior experience with advanced statistical and causal inference is a plus

Curious business attitude with a proven ability to seek projects with a sense of ownership

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 .

Client-provided location(s): Cupertino, CA
Job ID: apple-200619873-0836_rxr-658
Employment Type: OTHER
Posted: 2025-11-10T19:05:25

Perks and Benefits

  • Health and Wellness

    • Parental Benefits

      • Work Flexibility

        • Office Life and Perks

          • Vacation and Time Off

            • Financial and Retirement

              • Professional Development

                • Diversity and Inclusion

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