Job Description

Locations

• Seattle, Washington, United States 98117

Salary

Skills Required

• develop and maintain systemsintermediate
• assess quality and safety of AI/ML modelsintermediate
• create data pipelinesintermediate
• develop analytics toolsintermediate
• generate actionable insights from datasetsintermediate
• implement processes and frameworks for quality improvementintermediate
• architect scalable backend systemsintermediate
• implement scalable backend systemsintermediate
• support measurement and optimizationintermediate
• ensure performance and reliabilityintermediate
• work with data scientistsintermediate
• work with frontend engineersintermediate
• work with product managersintermediate
• define metricsintermediate
• gather requirementsintermediate
• deliver impactful solutionsintermediate
• ensure backend services are scalableintermediate
• ensure backend services are efficientintermediate
• ensure backend services are secureintermediate
• handle large volumes of dataintermediate
• enhance measurement frameworksintermediate
• adopt best practicesintermediate
• integrate latest technology advancementsintermediate
• provide technical leadershipintermediate
• mentorship to junior engineersintermediate
• foster culture of excellenceintermediate
• continuous improvementintermediate

Required Qualifications

• 2+ years in backend engineering with extensive experience in large-scale software system design and implementation. (experience, 2 years)
• Proficiency in languages such as Python, Java, GoLang, C++ or Scala. (experience)
• Experience with distributed systems, databases (SQL/NoSQL), and cloud platforms (AWS, Azure, GCP). (experience)
• Proven track record of building high-quality, highly scalable backend software systems. (experience)
• Ability to tackle complex challenges, think critically, and deliver innovative solutions. (experience)
• Excellent communication skills and a team-oriented attitude, thriving in a collaborative and fast-paced environment. (experience)
• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field. (degree in master)

Preferred Qualifications

• Solid understanding of machine learning algorithms, model evaluation metrics, and data processing pipelines. (experience)
• Strong background in data engineering, including data pipeline development, ETL processes, and data warehousing. (experience)
• Previous experience in a high-growth tech company or similar environment. (experience)
• Active participation in open-source projects related to AI/ML or backend development. (experience)
• Familiarity with CI/CD pipelines, containerization (Docker, Kubernetes), and infrastructure as code. (experience)
• Ph.D. in a related field.Apple’s most important resource, our soul, is our people. Apple benefits help further the well-being of our employees and their families in meaningful ways. No matter where you work at Apple, you can take advantage of our health and wellness resources and time-away programs. We’re proud to provide stock grants to employees at all levels of the company, and we also give employees the option to buy Apple stock at a discount — both offer everyone at Apple the chance to share in the company’s success. You’ll discover many more benefits of working at Apple, such as programs that match your charitable contributions, reimburse you for continuing your education and give you special employee pricing on Apple products. (experience)

Responsibilities

• As a Backend Engineer - AIML Measurement, you will:
• - Develop and maintain systems to assess the quality and safety of Apple Intelligence, ensuring our AI/ML models meet the highest standards.
• - Create robust data pipelines and analytics tools to generate actionable insights from vast datasets, driving informed decision-making.
• - Implement processes and frameworks for the continuous quality improvement of Apple Intelligence, fostering excellence and reliability.
• - Architect and implement scalable backend systems that support measurement and optimization efforts, ensuring performance and reliability.
• - Work closely with data scientists, frontend engineers, product managers, and other stakeholders to define metrics, gather requirements, and deliver impactful solutions. - Ensure backend services are scalable, efficient, and secure, handling large volumes of data with ease.
• - Continuously seek ways to enhance measurement frameworks, adopting best practices and integrating the latest advancements in technology.
• - Provide technical leadership and mentorship to junior engineers, fostering a culture of excellence and continuous improvement.

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