Deep Learning Engineer - US
Focal Systems
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Posted:
July 31, 2023
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Remote
About the position
This job is for a Deep Learning Engineer who will be working remotely in North America. The role involves developing and validating deep neural network architectures for real-time image processing tasks. The engineer will also be responsible for staying updated with the latest deep learning techniques and implementing them into the company's networks and pipelines. The successful candidate should have a Masters or PhD in CS/EE, 2-6 years of experience in Machine Learning or Deep Learning, and expertise in training Convolutional Neural Networks (CNNs) using frameworks like Keras or Pytorch.
Responsibilities
- Develop state-of-the-art and novel deep neural network architectures
- Develop training & testing pipelines to assess the performance of architectures on relevant image processing tasks
- Keep up with deep learning literature and research publications in order to implement the latest techniques into our networks and pipelines
- Develop machine-learning algorithms on a breadth of software frameworks (Keras, TensorFlow, Torch) and deploy on a diversity of hardware platforms
- Masters or PhD in CS / EE or equivalent with stellar academic performance
- 2-6 years of direct Machine Learning or Deep Learning experience in a corporate environment (post academia)
- Significant experience training Convolutional Neural Networks (CNNs)
- Experience with Keras (Tensorflow) / Pytorch
- Training Deep Learning Computer Vision (DL CV) applications in a corporate environment
Requirements
- Masters or PhD in CS / EE or equivalent with stellar academic performance
- 2-6 years of direct Machine Learning or Deep Learning experience in a corporate environment (post academia)
- Significant experience training Convolutional Neural Networks (CNNs)
- Experience with Keras (Tensorflow) / Pytorch
- Training Deep Learning Computer Vision (DL CV) applications in a corporate environment
Benefits
- Competitive Salary & Attractive Stock
- Health Insurance
- Catered Lunches
- Paid Time Off
- Quarterly Team Retreats
- Education Grants