176 to 200 of 388 PyTorch Jobs

modal 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 serving. End-to-end MLOps experience, including CI/CD for ML, experiment tracking, model registries ...

modal 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 serving. End-to-end MLOps experience, including CI/CD for ML, experiment tracking, model registries ...

modal 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 serving. End-to-end MLOps experience, including CI/CD for ML, experiment tracking, model registries ...

modal 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 serving. End-to-end MLOps experience, including CI/CD for ML, experiment tracking, model registries ...

modal 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 serving. End-to-end MLOps experience, including CI/CD for ML, experiment tracking, model registries ...

modal 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 serving. End-to-end MLOps experience, including CI/CD for ML, experiment tracking, model registries ...

modal 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 serving. End-to-end MLOps experience, including CI/CD for ML, experiment tracking, model registries ...

modal 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 serving. End-to-end MLOps experience, including CI/CD for ML, experiment tracking, model registries ...

modal 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 serving. End-to-end MLOps experience, including CI/CD for ML, experiment tracking, model registries ...

modal 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 serving. End-to-end MLOps experience, including CI/CD for ML, experiment tracking, model registries ...

modal 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 serving. End-to-end MLOps experience, including CI/CD for ML, experiment tracking, model registries ...

modal 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 serving. End-to-end MLOps experience, including CI/CD for ML, experiment tracking, model registries ...

modal 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 serving. End-to-end MLOps experience, including CI/CD for ML, experiment tracking, model registries ...

modal 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 serving. End-to-end MLOps experience, including CI/CD for ML, experiment tracking, model registries ...

modal 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 serving. End-to-end MLOps experience, including CI/CD for ML, experiment tracking, model registries ...

modal 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 serving. End-to-end MLOps experience, including CI/CD for ML, experiment tracking, model registries ...

modal 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 serving. End-to-end MLOps experience, including CI/CD for ML, experiment tracking, model registries ...

modal 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 serving. End-to-end MLOps experience, including CI/CD for ML, experiment tracking, model registries ...

modal 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 serving. End-to-end MLOps experience, including CI/CD for ML, experiment tracking, model registries ...

modal 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 serving. End-to-end MLOps experience, including CI/CD for ML, experiment tracking, model registries ...

modal 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 serving. End-to-end MLOps experience, including CI/CD for ML, experiment tracking, model registries ...

modal 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 serving. End-to-end MLOps experience, including CI/CD for ML, experiment tracking, model registries ...

modal 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 serving. End-to-end MLOps experience, including CI/CD for ML, experiment tracking, model registries ...

modal 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 serving. End-to-end MLOps experience, including CI/CD for ML, experiment tracking, model registries ...

among others); OR equivalent work experience delivering state-of-the-art AI/ML solutions. Experience with at least one major deep learning framework (PyTorch, JAX, TensorFlow). Familiarity with machine learning literature and state-of-the-art approaches. Experience developing and delivering robust software solutions, including demonstrated advanced programming ...