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Browse vetted remote Keras positions — deep learning model development, neural network engineering, and production ML system roles at AI companies.
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I started this company three years ago in my spare bedroom with a camera, a used GPU, and a single client: a small vineyard in Portugal that wanted to...
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We research and productise reinforcement learning for robotic process automation. Specifically, we train agents to navigate complex digital workflows...
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Posted 6 months ago
We're building AI for autonomous systems — specifically training agents that make sequential decisions in complex, partially observable environments....
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Posted 6 months ago
We build a consumer app that allows anyone to photograph a skin lesion and receive an AI-assisted risk assessment — with triage guidance toward a derm...
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Posted 8 months ago
We build AI-assisted diagnostic tools for radiologists. Our current product analyses chest X-rays for abnormality detection. We're now expanding to CT...
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Role guide
Keras is the high-level deep learning API that makes neural network development accessible while remaining production-capable. Remote Keras jobs involve building and training neural network models for classification, regression, NLP, and computer vision. Keras 3 now supports PyTorch, TensorFlow, and JAX backends, making Keras skills broadly transferable.
Is Keras still relevant for remote deep learning jobs?
Yes. Keras 3 now supports multiple backends (TensorFlow, PyTorch, JAX) and is actively maintained. Many companies prefer Keras for its simplicity and productivity, especially for applied ML teams.
Should I learn Keras or PyTorch for remote ML engineering jobs?
Both. PyTorch is dominant in research and LLM engineering. Keras is preferred in teams prioritising rapid model development and TensorFlow integration. Many engineers know both.
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