Apple’s AI and Machine Learning org is seeking to solve real-world ML challenges by exploring new methods, challenging existing metrics and protocols, and developing new insightful practices for multi-modal models with strong agent and reasoning capabilities
Requirements
- Deep technical skills in one or more machine learning areas, such as computer vision, audio, combinatorial optimization, causality analysis, natural language processing, and deep learning
- Strong software development skills with proficiency in Python
- hands-on experience working with deep learning toolkits like PyTorch, TensorFlow, or JAX (one of)
- Deep understanding of multi-modal foundation models
- Staying up-to-date with emerging trends in generative AI and multi-modal LLMs
- The ability to formulate machine learning problems, design, experiment, implement, and communicate solutions effectively with multi-functional teams
- Demonstrated publication records in relevant conferences (e.g., CVPR, ICCV, ECCV, NeurIPS, ICML, ICLR, etc.)
Responsibilities
- innovating and applying innovative research in foundation models with a particular focus on audio data
- working across the full ML pipeline-from pre-training on large-scale unlabeled audio corpora to post-training evaluation and fine-tuning with task-specific datasets
- 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 better understand its influence on model behavior and outcomes
- 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
Other
- 5+ years of experience developing and evaluating ML applications, demonstrating a passion for understanding and improving model/data quality
- Track records of adopting ML to solve cross-disciplinary problems
- Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition
- Discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple’s Employee Stock Purchase Plan
- Relocation might be eligible for discretionary bonuses or commission payments
