76 to 88 of 88 XGBoost Jobs in the UK

Bring 0–2 years of ML engineering experience or a PhD with ML coursework Strong skills in Python and ML libraries (TensorFlow, XGBoost, scikit-learn, etc.) Experience with data prep, training, and model evaluation Bonus: contributions to ML benchmarks Must be U.S.-based Opportunity Details ~20 hours/week Remote ...

Bring 0–2 years of ML engineering experience or a PhD with ML coursework Strong skills in Python and ML libraries (TensorFlow, XGBoost, scikit-learn, etc.) Experience with data prep, training, and model evaluation Bonus: contributions to ML benchmarks Must be U.S.-based Opportunity Details ~20 hours/week Remote ...

Bring 0–2 years of ML engineering experience or a PhD with ML coursework Strong skills in Python and ML libraries (TensorFlow, XGBoost, scikit-learn, etc.) Experience with data prep, training, and model evaluation Bonus: contributions to ML benchmarks Must be U.S.-based Opportunity Details ~20 hours/week Remote ...

Bring 0–2 years of ML engineering experience or a PhD with ML coursework Strong skills in Python and ML libraries (TensorFlow, XGBoost, scikit-learn, etc.) Experience with data prep, training, and model evaluation Bonus: contributions to ML benchmarks Must be U.S.-based Opportunity Details ~20 hours/week Remote ...

Bring 0–2 years of ML engineering experience or a PhD with ML coursework Strong skills in Python and ML libraries (TensorFlow, XGBoost, scikit-learn, etc.) Experience with data prep, training, and model evaluation Bonus: contributions to ML benchmarks Must be U.S.-based Opportunity Details ~20 hours/week Remote ...

Bring 0–2 years of ML engineering experience or a PhD with ML coursework Strong skills in Python and ML libraries (TensorFlow, XGBoost, scikit-learn, etc.) Experience with data prep, training, and model evaluation Bonus: contributions to ML benchmarks Must be U.S.-based Opportunity Details ~20 hours/week Remote ...

Bring 0–2 years of ML engineering experience or a PhD with ML coursework Strong skills in Python and ML libraries (TensorFlow, XGBoost, scikit-learn, etc.) Experience with data prep, training, and model evaluation Bonus: contributions to ML benchmarks Must be U.S.-based Opportunity Details ~20 hours/week Remote ...

Bring 0–2 years of ML engineering experience or a PhD with ML coursework Strong skills in Python and ML libraries (TensorFlow, XGBoost, scikit-learn, etc.) Experience with data prep, training, and model evaluation Bonus: contributions to ML benchmarks Must be U.S.-based Opportunity Details ~20 hours/week Remote ...

Bring 0–2 years of ML engineering experience or a PhD with ML coursework Strong skills in Python and ML libraries (TensorFlow, XGBoost, scikit-learn, etc.) Experience with data prep, training, and model evaluation Bonus: contributions to ML benchmarks Must be U.S.-based Opportunity Details ~20 hours/week Remote ...

Bring 0–2 years of ML engineering experience or a PhD with ML coursework Strong skills in Python and ML libraries (TensorFlow, XGBoost, scikit-learn, etc.) Experience with data prep, training, and model evaluation Bonus: contributions to ML benchmarks Must be U.S.-based Opportunity Details ~20 hours/week Remote ...

Bring 0–2 years of ML engineering experience or a PhD with ML coursework Strong skills in Python and ML libraries (TensorFlow, XGBoost, scikit-learn, etc.) Experience with data prep, training, and model evaluation Bonus: contributions to ML benchmarks Must be U.S.-based Opportunity Details ~20 hours/week Remote ...

Bring 0–2 years of ML engineering experience or a PhD with ML coursework Strong skills in Python and ML libraries (TensorFlow, XGBoost, scikit-learn, etc.) Experience with data prep, training, and model evaluation Bonus: contributions to ML benchmarks Must be U.S.-based Opportunity Details ~20 hours/week Remote ...

members in identifying and addressing data science opportunities. Required Skills & Experience Strong proficiency in Python and ML libraries such as: pandas, NumPy, scikit-learn XGBoost, LightGBM, CatBoost TensorFlow, Keras, PyTorch Experience with model deployment and serving tools: ONNX, TensorRT, TensorFlow Serving, TorchServe Familiarity with ML lifecycle tools: MLflow, Kubeflow, Azure … solving skills and ability to work independently or in a team. Strong proficiency in Python and ML libraries such as: pandas, NumPy, scikit-learn XGBoost, LightGBM, CatBoost TensorFlow, Keras, PyTorch Experience with model deployment and serving tools: ONNX, TensorRT, TensorFlow Serving, TorchServe Familiarity with ML lifecycle tools: MLflow, Kubeflow, Azure ...