AIML - Sr Machine Learning Engineer, Data & Machine Learning Innovation



Software Engineering
Cupertino, CA, USA
Posted on Thursday, March 21, 2024


Weekly Hours: 40
Role Number:200540664
As part of Apple's AI and Machine Learning org, we inspire and create groundbreaking technology for large-scale ML systems, computer vision, natural language processing, and multi-modal understanding. The Data and Machine Learning Innovation (DMLI) team is looking for a passionate Machine Learning Engineer to explore new methods, challenge existing metrics or protocols, and develop new insightful practices that will change how we understand data and overcome real-world ML challenges. As a team member, you will work on some of the most ambitious technical challenges in the field. Your role will involve collaborating closely with our team of machine learning researchers, engineers, and data scientists. Together, you will spearhead groundbreaking research initiatives and develop transformative products designed to create a significant impact for billions of users worldwide.


As a Machine Learning (ML) Engineer, you will be entrusted with the critical role of innovating and applying state-of-the-art research in ML to tackle sophisticated data problems. The solutions you develop will significantly impact future Apple products and the broader ML development ecosystem. You will work with a multidisciplinary team to actively participate in the data-model co-design and co-development practice. Your responsibilities will extend to the design and development of a comprehensive data generation and curation framework for foundation models at Apple. You will also be responsible to create robust model evaluation pipelines, integral to the continuous improvement and assessment of foundation models. Additionally, this will entail an in-depth analysis of multi-modal data to underscore its influence on model performance. You will have the opportunity to showcase your groundbreaking research work by publishing and presenting at premier academic venues. Our work may span a variety of applications, including but not limited to: - Improving current products and future hardware platforms with ML data - Designing and implementing semi-supervised, self-supervised representation learning techniques for maximizing the power of both limited labeled data and large-scale unlabeled data. - Developing on-device intelligence and learning with strong privacy protections - Employing data selection techniques such as novelty detection, active learning, and core-set selection for diverse data types like images, 3D models, natural language, and audio. - Uncovering patterns in data, setting performance targets, and leveraging modern statistical and ML-based methods to model data distributions. This will aid in reducing redundancy and addressing out-of-distribution samples.

Minimum Qualifications

Key Qualifications

  • 5+ years of demonstrated experience with developing and evaluating ML applications, and in understanding and improving data quality.
  • Expertise in natural language processing, search and recommendation, and machine learning with a passion for data-centric machine learning.
  • Solid understanding in large language model domain.
  • Staying on top of emerging trends in generative AI and multi-modal LLM.
  • Strong programming skills and hands-on experience using the following languages or deep learning frameworks: Python, PyTorch, or Jax.
  • Strong problem-solving and communication skills

Preferred Qualifications

Education & Experience

Ph.D/MS degree in Machine Learning, Natural Language Processing, Computer Vision, Data Science, Statistics, related field; or equivalent experience.

Additional Requirements

Pay & Benefits

  • Apple is an equal opportunity employer that is committed to inclusion and diversity. We take affirmative action to ensure equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant.