Job Description

The Product Operations machine learning research team is seeking an Applied Scientist in machine learning to conduct research in advanced machine learning techniques to address domain-specific challenges in manufacturing. Research scientists on our team drive projects from ideation to validation, with the goal of improving our core advanced manufacturing capabilities through creating innovative technologies. Please apply even if you do not meet all of the qualifications for this role.

Description

The Apple Operations team ensures that ground breaking designs become industry-leading products. In this role you will join an advanced R&D team responsible for bringing cutting-edge innovations to high production impact in manufacturing. We improve core capabilities through applied research, with partners in academia and across Apple's research org. As an Applied Scientist in machine learning, your responsibility will be to drive research and innovations from ideation to impact. You will work closely with manufacturing 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 and explore innovative areas that can yield significant impact in manufacturing. You will have the opportunity to collaborate with internal and academic research partners and contribute to our org's comprehensive research strategy. Successful applicants are self-motivated, experienced, creative yet practical-minded 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.

Minimum Qualifications

Expertise in independently designing and implementing ML experiments - establishing appropriate metrics, benchmarks, milestones, and communicating results to stakeholders with varying levels of technical background Masters degree in Machine Learning Publication record commensurate with seniority

Preferred Qualifications

Track record of successful research and interest in one or more of the following: deep learning, domain adaptation, foundation models, generative models, embodied AI, physical AI, world models, etc. For new-grad applicants, at least one first author publication in top machine learning venue including ICML, NeurIPS, ICLR, ICML, IEEE Transactions on Pattern Analysis and Machine Intelligence, etc. Excellent communication and presentation skills Demonstrable collaborative software development skills, including design review and code review


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