Senior Applied ML Engineer, Graph Neural Network, ML Frontiers
Tasks
- Benchmark graph convolution layer in JAX
- Collaborate with clients and research partners
- Define applied research engineering and product roadmap priorities
- Develop feature development for machine learning research and production
- Develop interactive Colab component for model analysis
- Implement distributed graph sampling algorithm
Perks/Benefits
- N/A
Skills/Tech-stack
Artificial Intelligence | C++ | Colab | Data Structures | Data structures algorithms | Decision Trees | Distributed Systems | Graph Neural Networks | Graph Sampling | JAX | Machine Learning | Neural Networks | PyTorch | Python | TensorFlow
Education
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