Software Engineer, ML (Training and Inference)
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Die Stelle
Design and maintain automated workflows that trigger model retraining based on new data availability or performance signals.
Optimize distributed training jobs to maximize performance while minimizing costs and turnaround time.
Ensure total reproducibility by implementing rigorous versioning for data, code, and model artifacts.
Improve production-grade model performance, scalability, and robustness within a scalable computational platform.
Build and contribute to a world-class ML drug design research environment with scalable software and libraries.
Develop tools and libraries to enable large-scale ML experiments across thousands of accelerators.
Optimize distributed training jobs to maximize performance while minimizing costs and turnaround time.
Ensure total reproducibility by implementing rigorous versioning for data, code, and model artifacts.
Improve production-grade model performance, scalability, and robustness within a scalable computational platform.
Build and contribute to a world-class ML drug design research environment with scalable software and libraries.
Develop tools and libraries to enable large-scale ML experiments across thousands of accelerators.
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