Apple is seeking to develop groundbreaking cellular technologies by applying Artificial Intelligence (AI) / Machine Learning (ML) solutions to augment and enhance core cellular technologies for iPhone, iPad, Watch, and other wireless product lines.
Requirements
- Expertise in implementing different Machine Learning algorithms, one or more of Deep Learning, Reinforcement Learning, Tree-based models, Graphical Models, RNN/LSTM, Transformers.
- Experience building machine learning models trained on large datasets making use of industry-grade data & training pipelines.
- Strong proficiency in Python and ML frameworks (e.g., PyTorch or TensorFlow) for data pre-processing, ML model training, and hyper parameter tuning.
- Familiarity with embedded software development using C or C++.
- Knowledge of wireless/internet standards such as 3GPP 5G NR and 4G LTE and user plane protocols (SDAP/PDCP/RLC/MAC) is a huge plus.
- Understanding of protocols such as TCP/UDP/IP/QUIC/RRC/NAS is a plus.
- Familiarity with CI/CD tooling.
Responsibilities
- Architect & develop cellular AI/ML methods for enhancing different cellular SW components including Layer 1 control, data plane software and cellular protocol stack.
- Will help realize innovative ML-based features that have an impact on Apple products and user experience.
- Will use real-world datasets from consumer devices, explore innovative ML models that balance system KPI and complexity.
- Will drive design, development and commercialization throughout the product life cycle.
- Assess iOS/iPadOS/watchOS features in shipping products and identify new areas where AI/ML can be used to enhance end user experience.
Other
- Bachelors degree in Computer Science, Electrical Engineering, or equivalent majors.
- 3+ years industry experience in researching and developing AI / machine learning solutions for commercial products.
- Ability to communicate effectively, both written and verbal, with cross-functional teams.
- Masters or PhD degree in Computer Science, Electrical Engineering, or equivalent majors.
- Research and publication history in the AI/ML field (e.g., ICLR, NeurIPS, CVPR, ICCV/ECCV, industry lab publications)
