Job Details

Role Number: 200649453-3543

Summary

We are seeking an experienced Machine Learning Research Engineer with a strong background in data curation and evaluation for Large Language Models.

Description

Your responsibilities will extend to the design and development of a comprehensive data selection, curation and annotation framework for foundation models at apple. We are looking for people passionate about innovating and applying ML algorithms that enable us to create high-quality and impactful datasets. As part of this role, you will also build evaluation benchmarks and evaluation methodologies to measure capabilities of existing models, work on data curation pipelines to hillclimb on benchmarks, and develop training frameworks for fine-tuning Foundation Models.

Minimum Qualifications

• • Masters in Computer Science, Machine Learning or related field
• • Demonstrated expertise in computer vision, natural language processing, and machine learning with a passion for data-centric machine learning.
• • Deep understanding and expertise in foundation models.
• • Familiarity with 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.

Preferred Qualifications

• • Familiarity with end-to-end Machine Learning Lifecycle
• • Demonstrated evidence of prior experience and expertise in data-centric machine learning research
• • Strong problem-solving and communication skills
• • Experience with recent post-training methodologies including reinforcement learning
• • Ph.D in Machine Learning, Natural Language Processing, Computer Vision, Data Science, Statistics or related areas

Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote 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 (https://www.eeoc.gov/sites/default/files/2023-06/22-088_EEOC_KnowYourRights6.12ScreenRdr.pdf) .