Machine Learning Engineer
Apple
Full-time
On-site
San Diego, California, United States
The Apple Operations team ensures that ground breaking designs become industry-leading products. In this role you will join a small team at the heart of our manufacturing ML capabilities. Our R&D team is responsible for the core ML libraries that engineers use to train models for factory deployment. We improve core capabilities through applied research, with partners in academia and across Apple’s research org.
As an Applied Scientist in data mining and machine learning, your responsibility will be to drive your research from ideation to impact. You will work closely with manufacturing machine learning engineers around the world to understand the challenges and opportunities in the field. You’ll leverage your research experience to propose and execute on promising approaches. You will have the opportunity to collaborate with internal and academic research partners and contribute to our org’s comprehensive research strategy.
On our team, we integrate successful research into robust pipelines that our partner teams leverage when training models. Successful applicants are self-motivated, experienced researchers, who are quick to build relationships and want to do impactful applied research. Exceptional candidates will demonstrate collaborative code practices, the ability to write and review production-quality code, and interest in training MLEs to apply novel approaches in the field.
- Expertise in independently designing and implementing ML experiments — establishing appropriate metrics, benchmarks, milestones, and communicating results to stakeholders with varying levels of technical background
- Ph.D. in Machine Learning from CS or ECE
- Publication record commensurate with seniority
- Track record of successful research and interest in one or more of the following: weakly- and semi-supervised machine learning, domain adaptation, data efficiency, knowledge distillation, imbalanced classification and regression, tabular foundation models, etc.
- For new-grad applicants, at least one first author publication in top machine learning / data mining conferences including ICML, NeurIPS, ICLR, KDD, CIKM, ICDM, SDM, The Web Conference, etc.
- Excellent communication and presentation skills
- Demonstrable collaborative software development skills, including design review and code review