6 of 6 Remote Permanent XGBoost Jobs

Kinesis, EMR Machine Learning - Supervised Models: Naïve Bayes, Logistic Regression, SVM, Linear Regression, KNN - Tree-Based Models: Decision Trees, Random Forest, Gradient Boosted Trees, XGBoost - Unsupervised Models: K-Means, DBSCAN, Hierarchical Clustering Deep Learning - ANN, CNN, RNN, LSTM - Frameworks: TensorFlow (Gradient Tape), PyTorch NN, Keras Sequential NLP & Generative AI - NLTK ...

Kinesis, EMR Machine Learning - Supervised Models: Naïve Bayes, Logistic Regression, SVM, Linear Regression, KNN - Tree-Based Models: Decision Trees, Random Forest, Gradient Boosted Trees, XGBoost - Unsupervised Models: K-Means, DBSCAN, Hierarchical Clustering Deep Learning - ANN, CNN, RNN, LSTM - Frameworks: TensorFlow (Gradient Tape), PyTorch NN, Keras Sequential NLP & Generative AI - NLTK ...

design, development, testing, and deployment of data science and AI solutions Experience and understanding of applied machine learning techniques in Python (e.g. xgboost, regression, decision trees) Experience with physics modelling highly desirable Practical knowledge and experience of developing AI solutions using advanced machine learning techniques (e.g. reinforcement learning, deep learning ...

build these skills. Experience with: Automation of processes/pipelines for data, analytics or operations ML-specific Python libraries (e.g. pandas, scikit-learn, xgboost) Big data tooling (e.g. Snowflake/snowpark, pyspark) Cloud computing - especially Azure, where we deploy key parts of our platform The interview process: Our interview process ...

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 ...

monitor, and maintain applications in AWS. Tech Stack We use a mix of modern tools and languages: Languages: Python, Typescript, SQL ML Frameworks: PyTorch, XGBoost API Frameworks: FastAPI, Express.js Databases: Snowflake, Postgres Cloud: AWS Hybrid Work & Schedule This is a remote position, and you are free to work from anywhere … Final Q&A round, alignment on project. Proficiency Requirements Proficiency in Python Experience with training custom ML models using PyTorch and XGBoost Familiarity with API development Good understanding of relational databases and experience with querying and managing data Knowledge of version control systems (e.g., Git) B2+ English proficiency Nice ...