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Apple AIML - Machine Learning Researcher MLR 
United States, California, Cupertino 
742166950

15.06.2024
Description
In this position you will conduct cutting edge research in Machine Learning in collaboration with your colleagues in MLR. You will advance the state of the art in diverse topics such as generative models, language modeling, reinforcement learning, etc, by developing new techniques and demonstrating them on different domains such as speech, vision and language. An integral part of the job involves publishing of the results to top level ML conferences, and participating in the research community through conferences, workshops etc. You will also have the opportunity to collaborate with broader teams across Apple in the use of the latest ML techniques.
Minimum Qualifications
  • Demonstrated expertise in machine learning research.
  • Publication record in relevant conferences (e.g., NeurIPS, ICML, ICLR, AAAI, CVPR, ICCV, ECCV, ACL, EMNLP, etc).
  • Hands-on experience working with deep learning toolkits such as Tensorflow or PyTorch.
  • Strong mathematical skills in linear algebra and statistics.
  • Ability to formulate a research problem, design, experiment, implement and communicate solutions.
  • Ability to work in a diverse collaborative environment.
Preferred Qualifications
  • PhD, or equivalent practical experience, in Computer Science, or a related technical field.
Pay & Benefits
  • At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $170,700 and $256,500, and your base pay will depend on your skills, qualifications, experience, and location.Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.
  • 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.