Apple | ML Engineer, Applied Machine Learning | Cupertino, CA | United States | BigDataKB.com | 17 Oct 2022

• Note: We don’t require that you have experience with all of these, but it is directly relevant to the role
• Significant experience building production level data and ML driven applications
• Strong sense of ownership, responsibility and accountability for the work and ability to manage own time and scope
• Expert knowledge of Python, data processing libraries (e.g. Pandas or Spark), machine learning libraries (e.g. PyTorch, Tensorflow or Keras) and tools (e.g. NumPy, Scikit-learn, etc)
• Previous history partnering with data scientists and transitioning a model from a research to production
• Extensive experience integrating ML models into production systems, including large data sources and services
• Experience optimizing and fine-tuning production ML models performance for both online real-time inference and offline batch processing
• Hands-on experience parallelizing and scaling data processing jobs to prepare and update training data sets and process and incorporate feedback
• Familiarity with one of the full lifecycle ML platforms (e.g. MLflow, SageMaker, etc.)
• Deep knowledge of statistics
• Experience with production level ML systems operations (MLops). E.g. CI/CD pipelines, unit and integration testing, containerization, monitoring and alerting, and production debugging, etc
• Knowledge and previous experience with NLP and time-series data is a plus

You will apply of your knowledge, experience, talent and creativity to connect all available Apple Support solutions and content with the user-behavioral data in a series of graphs to empower and drive user experiences and recommendations across multiple Support applications, detect potential issues with Apple products and services which might happening, and deeper understand customers journey funnel and ways to optimize it. You will be working very closely with product and data science teams to take their exploratory work, optimize and productionalize it while integrating with many data systems and application services. You will make sure to squeeze every single performance bit out of the ML models and will ensure it can reliably work in production under Apple load being easily monitored and debugged in production. Additionally, you will help shape the future and the roadmap of the family of the applications team owns, drive strong engineering excellence and culture, and see the effect of your work on Apple customers.

MS/PhD in Computer Science, Machine Learning, Math, Physics, Engineering or related field.