Machine Learning Engineer - Ad Platforms

Cupertino,California,United States

Machine Learning and AI

At Apple, we work every day to build products that enrich peoples 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 Apple News, the App Store, and on Apple TV+. Our platforms are highly performant, deployed at scale, and set new standards for enabling effective advertising while protecting user privacy. The Ad Platforms Data Insights team is seeking a machine learning engineer to join in developing the next generation of analytical solutions working with Engineering, Sales, Product, Marketing and Finance! In this role you will work as a key member of a data-centric team to drive the exploration, analysis, development, execution, and measurement of analytical solutions that're critical to running and growing the business.

Description

Responsibilities include turning the huge datasets generated by user searches, app content, and App Store context into business insights that improve the customer experience for the end-user as well as drive discovery and productivity for app developers. Do you have experience in applied research with expertise in pattern mining, anomaly detection, text analytics, predictive modeling, classification, and optimization? This role requires both broad knowledge of existing data mining algorithms and the creativity to invent and customize when necessary. You'll dig in and get into the details. The theory behind the techniques is just the beginning. You'll be working on projects where practical applications of these approaches get applied in real-world scenarios. Successful analytics teams involve data scientists and data engineers working hand in hand to build insightful and efficient solutions. In your role, you will be a key player in a multi-functional team that delivers insights that have direct and measurable impact. We're looking for a thoughtful, collaborative, and passionate person to join this amazing team! - Partner with Sales, Product, Marketing and the Executive Team to deliver analytics for product performance and customer insight - Develop end-to-end data solutions and reusable models and assets working closely with Data Technology team to ensure scalability and industrialization as models move into production - Own complete lifecycle of data products, including prototyping, deployment, ongoing maintenance and supporting downstream users. - Lead business analytics projects through all phases, including defining investigations, exploring data, conducting analysis, interpreting, and presenting results for stakeholders

Minimum Qualifications

• 6+ years of recent experience in a data science or machine learning engineering role.

• Programming skills in Python and SQL.

• Comfortable with cloud technologies such as AWS, Snowflake.

• Experience with Big Data tools such as Hadoop, Spark and PySpark.

• Experience in quantitative analysis including regression, classification, clustering, 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.

• Bachelor's in computer science, mathematics, or similar quantitative field

Key Qualifications

Preferred Qualifications

• Ability to operate comfortably and effectively in a fast-paced, multi-functional, constantly evolving environment.

• Familiarity with packages like sk-learn, XGBoost, PyTorch, JAX, etc.

• Familiarity with job orchestration frameworks like Airflow, CICD, model serving, scalability, Kubernetes, Docker, Jenkins.

• Experience in deep learning, LLM fine-tuning, and / or natural language processing.

• Experience in the digital advertising industry or related field.

• Graduate degree in computer science, mathematics, or similar quantitative field

Education & Experience

Additional Requirements

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 $143,100 and $264,200, 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 (https://www.apple.com/careers/us/benefits.html) 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.

• Apple is an equal opportunity employer that is committed to inclusion and diversity. We take affirmative action to ensure 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)

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