Machine Learning Engineer, II - App Engine (CUDA)
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El puesto
Implement and optimize software components for distributed execution of ML models on embedded GPU platforms.
Profile and optimize GPU utilization for ML workloads to reduce latency and boost throughput.
Contribute to message-passing, resource management, and runtime features for the App Engine SDK.
Collaborate with feature teams to validate App Engine functionality in vehicle and simulation environments.
Maintain clean, efficient C++ code and rigorous unit/integration tests.
Play a key role in performance-oriented development and embedded GPU programming in a fast-paced setting.
Profile and optimize GPU utilization for ML workloads to reduce latency and boost throughput.
Contribute to message-passing, resource management, and runtime features for the App Engine SDK.
Collaborate with feature teams to validate App Engine functionality in vehicle and simulation environments.
Maintain clean, efficient C++ code and rigorous unit/integration tests.
Play a key role in performance-oriented development and embedded GPU programming in a fast-paced setting.
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