Member of Technical Staff, Machine Learning
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El puesto
Build and improve ML components across data, training, evaluation, and inference in production environments.
Fine-tune and adapt models as part of larger systems while managing latency, cost, reliability, and safety constraints.
Develop and maintain data pipelines for real-world and synthetic data; ship iterative improvements driven by user feedback.
Implement rigorous evaluation and testing to understand model behavior and debug issues, performance problems, and incidents.
Write production-quality code in Python and work with PyTorch or JAX on GPU-backed infrastructure.
This hands-on role is for builders who want to ship real ML systems in production and grow ownership over time.
Fine-tune and adapt models as part of larger systems while managing latency, cost, reliability, and safety constraints.
Develop and maintain data pipelines for real-world and synthetic data; ship iterative improvements driven by user feedback.
Implement rigorous evaluation and testing to understand model behavior and debug issues, performance problems, and incidents.
Write production-quality code in Python and work with PyTorch or JAX on GPU-backed infrastructure.
This hands-on role is for builders who want to ship real ML systems in production and grow ownership over time.
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