Aiml - Machine Learning Researcher, Mlr

Apple Apple · Big Tech · Cambridge, MA · Machine Learning and AI

Apple is seeking a Machine Learning Researcher to conduct foundational research in LLMs and generative models, focusing on long-term, curiosity-driven projects. The role involves defining and executing research plans, implementing experiments, and publishing results in top-tier scientific venues. Collaboration with ML engineers and researchers across Apple is expected, with opportunities for technical mentorship.

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 focusing on LLMs and generative models.
  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, and publish your results in high-quality scientific venues.
  4. You will define your 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

  • PhD, or equivalent practical experience, in Computer Science, or related technical field
  • Demonstrated expertise in machine learning research.
  • Ability to formulate a research problem, design, experiment, implement and communicate solutions.
  • Publication record in relevant conferences (e.g., NeurIPS, ICML, ICLR, AISTATS, CVPR, ICCV, ECCV, ACL, EMNLP, etc).

Nice to have

  • Hands-on experience working with deep learning toolkits such as JAX, PyTorch or MLX
  • Proven industry experience
  • Strong mathematical skills in differential calculus, probability, statistics.
  • Strong coding skills, as exemplified by e.g. OSS contributions, and ability to maintain a coherent and evolving codebase.
  • Ability to work as a team player in a diverse collaborative environment.
  • You have proposed through previous publications impactful methods in areas of interest to the group, such as generative modeling (flow matching, diffusion, etc.), LLM/VLM training/fine-tuning/inference, neural network theory, or scaling laws.

What the JD emphasized

  • publication record in relevant conferences
  • impactful methods in areas of interest to the group, such as generative modeling (flow matching, diffusion, etc.), LLM/VLM training/fine-tuning/inference, neural network theory, or scaling laws

Other signals

  • ambitious curiosity-driven long-term research projects
  • foundational research in machine learning focusing on LLMs and generative models
  • publish your results in high-quality scientific venues
  • define your research plan to advance our understanding of machine learning and execute it through implementation and experimentation
  • technical mentorship and guidance