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Software Engineer, Pre - training/ai

Implement advanced dataset and model training techniques for the Daft data engine.
San Francisco, California, United States
Expert
1 week ago

✨ About The Role

- The role involves building model pretraining pipelines and developing benchmarks for AI data workloads. - Collaboration with the Daft data engine team is key to optimizing the data engine for modern AI workloads. - The candidate will stay at the forefront of AI research, incorporating the latest advancements into the data engine and platform capabilities. - Responsibilities include implementing advanced dataset and model training techniques, such as multimodal learning and synthetic data generation. - The position requires a principled and observable approach to building training and data pipelines.

⚡ Requirements

- The ideal candidate will have strong programming skills in Python and experience with deep learning frameworks such as PyTorch or TensorFlow. - A deep understanding of transformer architectures, self-supervised learning, and AI model training techniques is essential for success in this role. - Experience with distributed training frameworks and efficient model parallelism will be crucial for optimizing performance. - The candidate should possess expertise in data pipelines and large-scale dataset management, particularly with massive datasets over 100TB. - Familiarity with systems programming languages like Rust or C++ is a plus, indicating a well-rounded technical background. - A PhD or equivalent research experience in Machine Learning, Computer Science, or related fields is preferred, showcasing a strong academic foundation.
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Software Engineer, Pre - training/ai
San Francisco, California, United States
Engineering
About Eventual
Data Warehouse for Computer Vision