- Take a top-down approach towards system design starting from a use case of relevance to Apple wireless products defining a problem statement and arriving at groundbreaking innovative AI/ML-based solutions - Participate in cutting edge research in machine intelligence and wireless machine learning applications - Contribute to AI/ML framework design - Develop productivity-enhancing tools leveraging AI capabilities- Setup large-scale tests and deploy promising ideas quickly and broadly from creating experiments and prototyping implementations to designing new architectures developing solutions for real world large scale problems
BS and 3 years of relevant experience is required.
Excellent communication and presentation skills.
Direct experience on solving wireless interdisciplinary problems via machine learning (ML).
Demonstrated proficiency in Python with hands-on experience using data science libraries (pandas NumPy scikit-learn) for data manipulation and analysis.
Proven ability to navigate contribute to and maintain large-scale codebases with proper version control practices.
Ability to leverage AI/ML tools to streamline cellular research development and productization.
Practical experience implementing and optimizing neural network architectures using frameworks such as PyTorch or TensorFlow.
Knowledge in Algorithms Optimization Probability Statistics and Information Theory.
Working experience in one or more of the following research directions in Neural Networks: Deep Reinforcement Learning Federated Learning Transformer Transfer Learning Online Learning Generative Neural Network Graph Neural Network CNN RNN etc with demonstrated track-record of innovation in AI/ML Programming experience in Python MATLAB.
Demonstrate clarity of thought and strong analytical and problem-solving skills.
Ability to work well both independently and within a team.
Familiarity with the efficient implementation of AI/ML in hardware.
SQL skills for complex data querying manipulation and dataset creation/versioning for ML experiments.
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