Aiml - Machine Learning Researcher, Mlr

Apple Apple · Big Tech · Cupertino, CA +2 · Machine Learning and AI

This role is for a mid-level to senior Machine Learning Researcher focused on foundational, long-term, curiosity-driven research projects. The researcher will be expected to publish their work in top scientific venues and contribute to the advancement of machine learning understanding through implementation and experimentation. Collaboration with other researchers and engineers is key, with opportunities for technical mentorship and guidance.

What you'd actually do

  1. Play a part in building the next revolution of machine learning technology.
  2. In this role, you'll have the opportunity to work on innovative foundational research in machine learning.
  3. As a member of the team, you will be inspired by a diversity of challenging problems, collaborate with world-class machine learning engineers and researchers to impact the future of Apple products, and publish some of your results in high-quality scientific venues.
  4. You will propose your own research plan to advance our understanding of machine learning and execute it through implementation and experimentation, in collaboration with your colleagues.
  5. You will provide technical mentorship and guidance, and prepare technical reports for publication and conference talks.

Skills

Required

  • 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.

Nice to have

  • Ability to formulate a research problem, design, experiment, implement and communicate solutions.
  • Ability to work in a diverse collaborative environment.
  • PhD, or equivalent practical experience, in Computer Science, or related technical field.

What the JD emphasized

  • regularly publish your results in the main relevant conference and journal venues
  • make sure that your research results are of high quality and reproducible
  • Publication record in relevant conferences (e.g., NeurIPS, ICML, ICLR, AAAI, CVPR, ICCV, ECCV, ACL, EMNLP, etc).

Other signals

  • ambitious curiosity-driven long-term research projects
  • innovative foundational research
  • publish some of your results in high-quality scientific venues
  • regularly publish your results in the main relevant conference and journal venues
  • propose your own research plan to advance our understanding of machine learning and execute it through implementation and experimentation