AIML - Sr Machine Learning Engineer - Data and ML Innovation

About the Role

Key Responsibilities

• Innovating and applying research in foundation models with a focus on audio data, including working across the full ML pipeline from pre-training on large-scale unlabeled audio corpora to post-training evaluation and fine-tuning.
• Designing and developing a comprehensive multi-modal data generation and curation framework for foundation models at Apple.
• Building robust model evaluation pipelines that support continuous improvement and performance assessment.
• Analyzing multi-modal data to understand its influence on model behavior and outcomes.
• Showcasing research work by publishing and presenting at premier academic venues.
• Designing self-supervised and semi-supervised representation learning pipelines, and fine-tuning strategies for tasks like speech recognition and speaker identification.
• Applying data selection techniques such as novelty detection and active learning across multi modalities to improve data efficiency and reduce distributional gaps.
• Modeling data distributions using ML/statistical methods to uncover patterns, reduce redundancy, and handle out-of-distribution challenges.
• Guiding product teams in selecting effective ML solutions and rapidly learning new methods and domains as needed.

Requirements

• Deep technical skills in one or more machine learning areas such as computer vision, audio, natural language processing, deep learning, or causality analysis.
• Strong software development skills with proficiency in Python.
• Hands-on experience with deep learning toolkits like PyTorch, TensorFlow, or JAX.
• 5+ years of experience developing and evaluating ML applications.
• Passion for understanding and improving model and data quality.

Nice to Have

• Deep understanding of multi-modal foundation models.
• Staying up-to-date with emerging trends in generative AI and multi-modal LLMs.
• Ability to formulate machine learning problems, design, experiment, implement, and communicate solutions effectively with multi-functional teams.
• Demonstrated publication record in relevant conferences such as CVPR, ICCV, ECCV, NeurIPS, ICML, ICLR.
• Track record of applying ML to solve cross-disciplinary problems.

Qualifications

• Educational background or certifications are not explicitly specified, but extensive experience in ML is required.

Benefits & Perks

• Base pay between $139,500 and $258,100, depending on skills, qualifications, experience, and location.
• Opportunity to become an Apple shareholder through stock programs.
• Discretionary restricted stock unit awards and stock purchase plans.
• Comprehensive medical and dental coverage.
• Retirement benefits.
• Discounted products and free services.
• Reimbursement for educational expenses.
• Potential eligibility for bonuses, commissions, and relocation assistance.