Develop and maintain systems to assess the quality and safety of Apple Intelligence, ensuring AI/ML models meet the highest standards.
Requirements
- 2+ years in backend engineering with extensive experience in large-scale software system design and implementation.
- Proficiency in languages such as Python, Java, GoLang, C++ or Scala.
- Experience with distributed systems, databases (SQL/NoSQL), and cloud platforms (AWS, Azure, GCP).
- Proven track record of building high-quality, highly scalable backend software systems.
- Ability to tackle complex challenges, think critically, and deliver innovative solutions.
- Solid understanding of machine learning algorithms, model evaluation metrics, and data processing pipelines.
- Familiarity with CI/CD pipelines, containerization (Docker, Kubernetes), and infrastructure as code.
Responsibilities
- 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.
Other
- Provide technical leadership and mentorship to junior engineers, fostering a culture of excellence and continuous improvement.
- Excellent communication skills and a team-oriented attitude, thriving in a collaborative and fast-paced environment.
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
- Previous experience in a high-growth tech company or similar environment.
- Ph.D. in a related field.
