Software Engineer – Full Stack, AMP Data Science & Analytics
Santa Clara Valley (Cupertino), California, United States
Software and Services
At Apple, phenomenal ideas have a way of becoming great products, services, and customer experiences very quickly. If you are an ambitious, high-energy individual who is not afraid of challenges, we’re looking for you. Apple is seeking an experienced Software Engineer who are passionate about Machine Learning related applications for Apple Media Products (AMP), covering the App Store, Arcade, Apple Music/iTunes, Video, TV and other services to join AMP Data Science & Analytics team. You will dive deep into AMP’s internet-scale data to build machine learning services and products that will improve the entire analytics efforts.
- 2+ years of experience working in Software Engineer related role. You should have a strong and curious mind with an ability to transfer complex requirements and technical challenges into solid implementations.
- Strong object-oriented design and programming skills in one of the programming languages: Python, Java.
- Hands-on experience with big data technologies such as SQL, Hive, Hadoop and Spark.
- Knowledge in machine learning preferred.
- Full-stack development experience (e.g., UI, Service and APIs) for Python application preferred.
- Excellent communication skills with meticulous attention to detail.
- Good team player.
We are looking for candidates with strong engineering skills to help build end-to-end Machine Learning related products and services. This role will work on both adding new features to our engineering system and improving the engineering excellence of existing products. You will also have the opportunities to bring state-of-art machine learning models/solutions into real application and make impact. The team’s culture is centered around rapid iteration with open feedback and debate along the way, plus strong collaboration with data science and business partners to deliver sound engineering solutions.
Education & Experience
Master’s degree in Computer Science, Statistics, Engineering or other relevant field with equivalent technical experiences.