Machine Learning Research Engineer

Apple

5d

About The Position

The Product Operations machine learning team is seeking a machine learning research engineer to conduct research in anomaly detection and automated machine learning to address domain-specific challenges in manufacturing multi-modal data that includes time-series, graph, image and/or tabular data. Research engineers on our team drive projects from ideation to validation, with the goal of improving our core manufacturing ML capabilities. They support ML software engineers in translating successful approaches to production code, and train MLEs to apply them to factory use cases. 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 a Research Engineer, 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.

Requirements

• Ph.D. in Machine Learning from CS or ECE
• Publication record commensurate with seniority
• Track record of successful research
• Expertise in independently designing and implementing ML experiments — establishing appropriate metrics, benchmarks, milestones, and communicating results to stakeholders with varying levels of technical background
• Excellent communication and presentation skills
• Demonstrable collaborative software development skills, including design review and code review

Nice To Haves

• 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.
• Collaborative code practices
• Ability to write and review production-quality code
• Interest in training MLEs to apply novel approaches in the field

Responsibilities

• Drive research from ideation to impact.
• Work closely with manufacturing machine learning engineers around the world to understand challenges and opportunities.
• Leverage research experience to propose and execute on promising approaches.
• Collaborate with internal and academic research partners.
• Contribute to the organization’s comprehensive research strategy.
• Integrate successful research into robust pipelines for partner teams.
• Design and implement ML experiments, establishing appropriate metrics, benchmarks, and milestones.
• Communicate results to stakeholders with varying levels of technical background.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: Ph.D. or professional degree