Machine Learning Researcher, MLR

Apple Inc.
Cambridge, United Kingdom
4 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English

Job location

Cambridge, United Kingdom

Tech stack

Artificial Neural Networks
Machine Learning
Performance Tuning
PyTorch
Large Language Models
Deep Learning
Information Technology
AISTATS
Stable Diffusion
Software Coding

Job description

You have a strong research background in machine learning or related fields, and regularly publish your results in the main relevant conferences, and make sure that your research results are of high quality and reproducible. 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. You will provide technical mentorship and guidance, and prepare technical reports for publication and conference talks. You will have the opportunity to collaborate with broader teams across Apple.

Requirements

  • 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)., * 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.

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