Machine Learning Engineer - II
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The role
Develop and maintain end-to-end ML features for a graphics-focused product, from concept to release.
Work hands-on on the ML lifecycle, including data analysis, model training, evaluation, and deployment.
Apply strong ML fundamentals and AI knowledge to real-world computer vision and graphics challenges.
Leverage data analysis tools (Jupyter, NumPy, Matplotlib) and synthesize data for training.
Write reliable, secure, and high-performance code in C/C++ and Python, using DL frameworks such as TensorFlow, PyTorch, Keras, Caffe, or Torch.
Collaborate with cross-functional teams on architecture, design reviews, and documentation, guiding projects from specs to release.
Work hands-on on the ML lifecycle, including data analysis, model training, evaluation, and deployment.
Apply strong ML fundamentals and AI knowledge to real-world computer vision and graphics challenges.
Leverage data analysis tools (Jupyter, NumPy, Matplotlib) and synthesize data for training.
Write reliable, secure, and high-performance code in C/C++ and Python, using DL frameworks such as TensorFlow, PyTorch, Keras, Caffe, or Torch.
Collaborate with cross-functional teams on architecture, design reviews, and documentation, guiding projects from specs to release.
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