AI/ML - Machine Learning Engineer, Machine Translation

Santa Clara Valley (Cupertino), California, United States
Machine Learning and AI

Summary

Posted:
Weekly Hours: 40
Role Number:200129916
The AI/ML - Machine Translation team is looking for exceptional Machine Learning Engineers passionate about delivering delightful customer experiences around Machine Translation. The opportunities include developing a cutting edge run-time system, pushing the envelope on machine learning inference and deploying AI using embedded and distributed computing to benefit millions of users.

Key Qualifications

  • Strong expertise in C++ and Python
  • Experience in object-oriented software design and programming of large-scale run-time systems
  • Experience In Deploying User-Facing Machine Learning Systems In Production
  • Knowledge of embedded and distributed systems
  • Knowledge of machine learning techniques and hands-on experience with ML toolkits like TensorFlow or PyTorch is a plus
  • Outstanding Spoken And Written Communication Skills

Description

You will be a part of a cross-functional team that has ambitious goals of enabling our customers to communicate across language barriers using machine translation technology. You will be responsible for a wide variety of research and development activities in machine learning systems including rapid prototyping, optimizing inference on current and future Apple platforms and building large-scale, distributed systems. We are looking for ML engineers who can envision end-to-end solutions and collaborate with designers, ML researchers and system engineers to bring research ideas to production. To succeed in this role, you should be an excellent programmer and a creative problem solver, who enjoys learning new things, improving existing processes, and contributing to overall system design. You should also be a phenomenal teammate who thrives in a dynamic environment with rapidly changing priorities.

Education & Experience

B.S. or M.S. in Computer Science or related field.

Additional Requirements