Apple | Machine Learning Engineer, Modeling Team – SPG | Cupertino, CA | United States | BigDataKB.com | 11/14/2022

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Job Location: Cupertino, CA

Summary

Posted: Mar 10, 2022
Role Number:200355028
Apple is looking for world-class qualified ML/Deep Learning engineers to develop, debug, improve and integrate machine learning technologies within our Modeling Team branch of the Special Projects Group, focusing on autonomous technologies.

Key Qualifications

  • 3+ years of experience using ML technologies, such as PyTorch, TensorFlow, Jax, Theano,..
  • 3+ years experience in ML and deep learning (DL)
  • Expert in Python and with a minimum of 5+ years using this language
  • Knowledge of probabilities and algebra typically used in machine learning and data analysis
  • Experience researching current DL literature: optimization methods, common types of models and layers, etc.
  • Understanding of modern machine learning concepts and state of the art deep learning frameworks
  • Proven ability to train and debug deep learning systems: Define metrics and datasets, performing error analysis, training models in a modern DL framework
  • Excellent communication skills — you collaborate effectively with other teams and communicate clearly about your work
  • Creative, collaborative, passionate and detail-oriented
  • Preferred to have experience with hardware specific optimization of ML models and deployment
  • Preferred to have experience specifically in applying deep learning to robotics problems and predicting multimodal behaviors for agents
  • Preferred to have experience with some of the following topics: CNNs, GNNs, Transformers, RNNs, LSTMs, fully-supervised learning, semi-supervised learning, active learning, domain adaptation, reinforcement learning, imitation learning, Generative Adversarial Networks (GANs), Markov Models

Description

As a member of the team, you will work on a hardware/software project enabled by the ML technologies you build. Our team pursues research & development in the areas of machine learning (ML) with a particular focus on deep learning (DL), optimization, and reinforcement learning (RL). • Oversee deep learning projects from dataset generation and preprocessing to machine learning algorithms design and metric analysis • Design and implement new state-of-the-art algorithms, integrate and improve existing pipelines • Ship and deploy ML models. Analyze metrics of ML models. • Stay current on latest ML algorithms and optimize ML systems under timing constraints • Present research results in internal talks

Education & Experience

Additional Requirements




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