25 of 25 Remote XGBoost Jobs

development, with practical experience across model development, testing and deployment. Experience with machine learning frameworks and libraries such as PyTorch, TensorFlow, scikit-learn, XGBoost or equivalent. Practical knowledge of Generative AI techniques, including large language models, prompt engineering, retrieval-augmented generation, model evaluation and responsible AI considerations. Understanding of MLOps ...

development, with practical experience across model development, testing and deployment. Experience with machine learning frameworks and libraries such as PyTorch, TensorFlow, scikit-learn, XGBoost or equivalent. Practical knowledge of Generative AI techniques, including large language models, prompt engineering, retrieval-augmented generation, model evaluation and responsible AI considerations. Understanding of MLOps ...

development, with practical experience across model development, testing and deployment. Experience with machine learning frameworks and libraries such as PyTorch, TensorFlow, scikit-learn, XGBoost or equivalent. Practical knowledge of Generative AI techniques, including large language models, prompt engineering, retrieval-augmented generation, model evaluation and responsible AI considerations. Understanding of MLOps ...

development, with practical experience across model development, testing and deployment. Experience with machine learning frameworks and libraries such as PyTorch, TensorFlow, scikit-learn, XGBoost or equivalent. Practical knowledge of Generative AI techniques, including large language models, prompt engineering, retrieval-augmented generation, model evaluation and responsible AI considerations. Understanding of MLOps ...

development, with practical experience across model development, testing and deployment. Experience with machine learning frameworks and libraries such as PyTorch, TensorFlow, scikit-learn, XGBoost or equivalent. Practical knowledge of Generative AI techniques, including large language models, prompt engineering, retrieval-augmented generation, model evaluation and responsible AI considerations. Understanding of MLOps ...

development, with practical experience across model development, testing and deployment. Experience with machine learning frameworks and libraries such as PyTorch, TensorFlow, scikit-learn, XGBoost or equivalent. Practical knowledge of Generative AI techniques, including large language models, prompt engineering, retrieval-augmented generation, model evaluation and responsible AI considerations. Understanding of MLOps ...

hands-on experience developing, training, and deploying machine learning models.Practical experience with leading AI/ML frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn, XGBoost), including model selection, tuning, and evaluation.Experience implementing end-to-end machine learning workflows, including data preprocessing, feature engineering, model development, validation, and deployment to production ...

hands-on experience developing, training, and deploying machine learning models.Practical experience with leading AI/ML frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn, XGBoost), including model selection, tuning, and evaluation.Experience implementing end-to-end machine learning workflows, including data preprocessing, feature engineering, model development, validation, and deployment to production ...

hands-on experience developing, training, and deploying machine learning models.Practical experience with leading AI/ML frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn, XGBoost), including model selection, tuning, and evaluation.Experience implementing end-to-end machine learning workflows, including data preprocessing, feature engineering, model development, validation, and deployment to production ...

hands-on experience developing, training, and deploying machine learning models.Practical experience with leading AI/ML frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn, XGBoost), including model selection, tuning, and evaluation.Experience implementing end-to-end machine learning workflows, including data preprocessing, feature engineering, model development, validation, and deployment to production ...

hands-on experience developing, training, and deploying machine learning models.Practical experience with leading AI/ML frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn, XGBoost), including model selection, tuning, and evaluation.Experience implementing end-to-end machine learning workflows, including data preprocessing, feature engineering, model development, validation, and deployment to production ...

hands-on experience developing, training, and deploying machine learning models.Practical experience with leading AI/ML frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn, XGBoost), including model selection, tuning, and evaluation.Experience implementing end-to-end machine learning workflows, including data preprocessing, feature engineering, model development, validation, and deployment to production ...

based machine learning services using one or more cloud providers (preferably GCP) Excellent understanding of classical Machine Learning algorithms (e.g. Logistic Regression, Random Forest, XGBoost, etc.) and modern Deep Learning algorithms (e.g. BERT, LSTM, etc.) Strong knowledge of SQL and Python's ecosystem for data analysis (Jupyter, Pandas, Scikit Learn ...

another modern programming language used for data science and machine learning development.Practical experience with machine learning frameworks and libraries such as scikit-learn, XGBoost, PyTorch, TensorFlow or equivalent.Experience across the end-to-end ML lifecycle, including data preparation, feature engineering, model development, validation, deployment, monitoring and optimisation.Understanding of MLOps ...

another modern programming language used for data science and machine learning development.Practical experience with machine learning frameworks and libraries such as scikit-learn, XGBoost, PyTorch, TensorFlow or equivalent.Experience across the end-to-end ML lifecycle, including data preparation, feature engineering, model development, validation, deployment, monitoring and optimisation.Understanding of MLOps ...

another modern programming language used for data science and machine learning development.Practical experience with machine learning frameworks and libraries such as scikit-learn, XGBoost, PyTorch, TensorFlow or equivalent.Experience across the end-to-end ML lifecycle, including data preparation, feature engineering, model development, validation, deployment, monitoring and optimisation.Understanding of MLOps ...

another modern programming language used for data science and machine learning development.Practical experience with machine learning frameworks and libraries such as scikit-learn, XGBoost, PyTorch, TensorFlow or equivalent.Experience across the end-to-end ML lifecycle, including data preparation, feature engineering, model development, validation, deployment, monitoring and optimisation.Understanding of MLOps ...

another modern programming language used for data science and machine learning development.Practical experience with machine learning frameworks and libraries such as scikit-learn, XGBoost, PyTorch, TensorFlow or equivalent.Experience across the end-to-end ML lifecycle, including data preparation, feature engineering, model development, validation, deployment, monitoring and optimisation.Understanding of MLOps ...

understanding of computer science fundamentals and time-series forecasting. Machine Learning: Strong grasp of ML and deep learning algorithms (e.g. Logistic Regression, Random Forest, XGBoost, BERT, LSTM, NLP, Transfer Learning). Reasonable Adjustments: Respect and equality are core values to us. We are proud of the diverse and inclusive community ...

team. What We're Looking For Strong commercial experience developing machine learning solutions using Python. Experience with frameworks such as: PyTorch TensorFlow Scikit-learn XGBoost Experience deploying ML solutions on AWS, including services such as SageMaker, Lambda, and S3. Strong understanding of MLOps tooling, including MLflow, Weights & Biases, or Data ...

highly regulated environment Advanced Python and SQL skills Experience building predictive models from development through to deployment Knowledge of machine learning techniques such as XGBoost, CatBoost or similar approaches Ability to work with large, complex and messy datasets Strong stakeholder engagement and communication skills Experience supporting or mentoring more junior ...

operating models on DatabricksFamiliarity in Cloud-based application development (we use AWS & Azure)Familiarity with one or more ML frameworks and technologies: scikit-learn, xgboost, TensorFlow, PyTorch, Spark, SageMaker, Vertex AI, Kubeflow, Seldon, TritonStrong communication skills, able to express ideas clearly and collaborate across teamsAdditional InformationBring ...

End DateMonday 24 August 2026Salary Range72,702 - 80,780We support flexible working – click here for more information on flexible working optionsFlexible Working OptionsJob ShareJob Description Summary.Job DescriptionJOB TITLE: Senior Machine Learning & AI Engineer - Consumer Data ...

End DateMonday 24 August 2026Salary Range72,702 - 80,780We support flexible working – click here for more information on flexible working optionsFlexible Working OptionsJob ShareJob Description Summary.Job DescriptionJOB TITLE: Senior Machine Learning & AI Engineer - Consumer Data ...

Who are we Tripledot Studios is one of the largest independent mobile games companies in the world.We are a multi-award-winning organisation, with a global 2,500+ strong team across 12 studios.Our expanded portfolio ...