AIML - Machine Learning Engineer, ASR Infrastructure and Tools Team

Cambridge, Massachusetts, United States
Machine Learning and AI


Weekly Hours: 40
Role Number:200527963
You will be part of a cross functional team that works between researchers and cloud technology teams building a highly scalable ASR focused ML platform. Your work will be used to reliably train thousands of models every week and deliver those models to millions of customers. You will use the latest open source technologies like PyTorch, HuggingFace, K8s as well as the latest Apple Silicon and Apple hardware to deliver the best experience for our customers.


You will be a part of a team that's responsible for a wide variety of speech-related development activities, including acoustic modeling, language modeling and tools development. Our speech recognition research is typically data driven and we are particularly passionate about unsupervised and supervised techniques to leverage large quantities of data. You should be passionate about building phenomenal products. Because you'll be working closely with researchers and engineers from a number of other teams at Apple, you’re a standout colleague who thrives in a collaborative environment.

Minimum Qualifications

Key Qualifications

  • 5+ years working experience with large distributed systems (Spark, K8s)
  • Familiarity with large-scale data processing and distributed systems
  • Experience with various audio formats and manipulation techniques
  • Strong coding skills in Python, C/C++, or Java
  • Experience with software engineering best practices
  • Knowledge of Machine Learning concepts and toolkits (PyTorch)
  • Hard working and detail oriented individual who will have a profound impact in making Siri better every single day

Preferred Qualifications

Education & Experience

Bachelors or Masters/PhD in Computer Science or Engineering or a related field, or equivalent experience.

Additional Requirements

  • Apple is an equal opportunity employer that is committed to inclusion and diversity. We take affirmative action to ensure equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant.