Software Engineer in Machine Learning

Santa Clara Valley (Cupertino), California, United States
Software and Services

Summary

Posted:
Weekly Hours: 40
Role Number:200171392
Join the team responsible for Apple’s Beta Software Program! Our app, Feedback Assistant, collects user feedback on beta OS software releases, while our internal tools analyze, group, and send impactful feedback to Apple's engineering teams. We are looking for engineers to apply machine learning approaches to making the most out of our feedback.

Key Qualifications

  • Experience designing and training machine learning models to tackle critical business problems
  • Proficiency training large scale models using modern machine learning frameworks (e.g. TensorFlow, PyTorch)
  • Experience in machine learning, deep learning, information retrieval, natural language processing or data mining
  • Strong fundamentals in problem solving, algorithm design, and model building
  • Excellent verbal and written communication and presentation skills

Description

As a Software Engineer in Machine Learning, you will investigate innovative machine learning algorithms with the goal of amplifying the impact of our customer feedback. You will pursue research and prototype designs to suggest innovative approaches. To implement these designs, you'll implement data cleanup and preprocessing pipelines, infrastructure to support model training, and systems to visualize the results. Your duties will vary, but may include: Building end-to-end tools to make use of our extensive dataset Deciding between machine learning and data analysis approaches to tackle problems Directing research to align with the constraints of our production system Working with large scale computing frameworks, data analysis systems and modeling environments Using current programming languages and technologies to translate algorithms and technical specifications into code Participating in the strong ML community at Apple

Education & Experience

Bachelor’s degree or higher in Computer Science or equivalent field, proven experience

Additional Requirements