6 of 6 Remote/Hybrid Metadata Jobs in Suffolk

development of AI solutions using Computer Vision, Machine Learning, Generative AI, and data science to enable capabilities such as automated sports metadata generation and detection of key events in live content and data streams." Generate actionable insights for player performance, contextual statistics, and injury risk by designing models with embedded … knowledge of modern ML techniques, including Generative AI, and how emergent models can extract insights from multimodal sports data (e.g., numerical, spatial, video, or metadata)." Advanced Python" expertise "with strong"hands-on"use of ML/DL frameworks (e.g.," PyTorch , TensorFlow), including taking models from experimentation into production model ...

development of AI solutions using Computer Vision, Machine Learning, Generative AI, and data science to enable capabilities such as automated sports metadata generation and detection of key events in live content and data streams." Generate actionable insights for player performance, contextual statistics, and injury risk by designing models with embedded … knowledge of modern ML techniques, including Generative AI, and how emergent models can extract insights from multimodal sports data (e.g., numerical, spatial, video, or metadata)." Advanced Python" expertise "with strong"hands-on"use of ML/DL frameworks (e.g.," PyTorch , TensorFlow), including taking models from experimentation into production model ...

development of AI solutions using Computer Vision, Machine Learning, Generative AI, and data science to enable capabilities such as automated sports metadata generation and detection of key events in live content and data streams." Generate actionable insights for player performance, contextual statistics, and injury risk by designing models with embedded … knowledge of modern ML techniques, including Generative AI, and how emergent models can extract insights from multimodal sports data (e.g., numerical, spatial, video, or metadata)." Advanced Python" expertise "with strong"hands-on"use of ML/DL frameworks (e.g.," PyTorch , TensorFlow), including taking models from experimentation into production model ...

development of AI solutions using Computer Vision, Machine Learning, Generative AI, and data science to enable capabilities such as automated sports metadata generation and detection of key events in live content and data streams." Generate actionable insights for player performance, contextual statistics, and injury risk by designing models with embedded … knowledge of modern ML techniques, including Generative AI, and how emergent models can extract insights from multimodal sports data (e.g., numerical, spatial, video, or metadata)." Advanced Python" expertise "with strong"hands-on"use of ML/DL frameworks (e.g.," PyTorch , TensorFlow), including taking models from experimentation into production model ...

development of AI solutions using Computer Vision, Machine Learning, Generative AI, and data science to enable capabilities such as automated sports metadata generation and detection of key events in live content and data streams." Generate actionable insights for player performance, contextual statistics, and injury risk by designing models with embedded … knowledge of modern ML techniques, including Generative AI, and how emergent models can extract insights from multimodal sports data (e.g., numerical, spatial, video, or metadata)." Advanced Python" expertise "with strong"hands-on"use of ML/DL frameworks (e.g.," PyTorch , TensorFlow), including taking models from experimentation into production model ...

development of AI solutions using Computer Vision, Machine Learning, Generative AI, and data science to enable capabilities such as automated sports metadata generation and detection of key events in live content and data streams." Generate actionable insights for player performance, contextual statistics, and injury risk by designing models with embedded … knowledge of modern ML techniques, including Generative AI, and how emergent models can extract insights from multimodal sports data (e.g., numerical, spatial, video, or metadata)." Advanced Python" expertise "with strong"hands-on"use of ML/DL frameworks (e.g.," PyTorch , TensorFlow), including taking models from experimentation into production model ...