Foundation Model ML Engineer - Autonomous Driving Job at Didi Labs in San Jose
Didi Labs, San Jose, CA, United States
A leading technology company in San Jose is seeking a Machine Learning Engineer specializing in foundation models to develop AI systems for autonomous vehicles. The role involves designing and training large-scale deep learning models, optimizing for real-world deployment, and collaborating with cross-functional teams to enhance multi-agent behavior prediction. The ideal candidate has a strong background in machine learning and coding experience in Python and C++. This role offers a competitive salary range and additional benefits for contributions to cutting-edge technology.
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In Summary: A leading technology company in San Jose is seeking a Machine Learning Engineer specializing in foundation models to develop AI systems for autonomous vehicles . The role involves designing and training large-scale deep learning models, optimizing for real-world deployment . The ideal candidate has a strong background in machine learning and coding experience in Python and C++ .
En Español: Una empresa tecnológica líder en San José está buscando un ingeniero de aprendizaje automático especializado en modelos fundacionales para desarrollar sistemas de IA para vehículos autónomos. El papel involucra el diseño y capacitación de modelos de inteligencia artificial a gran escala, la optimización para el despliegue del mundo real y la colaboración con equipos interfuncionales para mejorar la predicción del comportamiento multi-agente.
#J-18808-Ljbffr
In Summary: A leading technology company in San Jose is seeking a Machine Learning Engineer specializing in foundation models to develop AI systems for autonomous vehicles . The role involves designing and training large-scale deep learning models, optimizing for real-world deployment . The ideal candidate has a strong background in machine learning and coding experience in Python and C++ .
En Español: Una empresa tecnológica líder en San José está buscando un ingeniero de aprendizaje automático especializado en modelos fundacionales para desarrollar sistemas de IA para vehículos autónomos. El papel involucra el diseño y capacitación de modelos de inteligencia artificial a gran escala, la optimización para el despliegue del mundo real y la colaboración con equipos interfuncionales para mejorar la predicción del comportamiento multi-agente.