1 to 25 of 75 XGBoost Jobs

to stand out? Consulting Experience Databricks Machine Learning Associate or Machine Learning Professional Certification. Familiarity with traditional machine learning tools such as Python, SKLearn, XGBoost, SparkML, etc. Experience with deep learning frameworks like TensorFlow or PyTorch. Knowledge of ML model deployment options (e.g., Azure Functions, FastAPI, Kubernetes) for real-time More ❯

computer science fundamentals, including data structures, algorithms, data modelling, and software architecture Solid understanding of classical Machine Learning algorithms (e.g., Logistic Regression, Random Forest, XGBoost, etc.), state-of-the-art research areas (e.g., NLP, Transfer Learning, etc.), and modern Deep Learning algorithms (e.g., BERT, LSTM, etc.) Solid knowledge of SQL More ❯

computer science fundamentals, including data structures, algorithms, data modelling and software architecture Solid understanding of classical Machine Learning algorithms (e.g. Logistic Regression, Random Forest, XGBoost, etc), state-of-the-art research areas (e.g. NLP, Transfer Learning etc) and modern Deep Learning algorithms (e.g. BERT, LSTM, etc) Solid knowledge of SQL More ❯

with large datasets and with streaming data architectures. Demonstrated knowledge of large language models and generative AI. ML frameworks (Scikit-Learn, NumPy, SciPy, Pandas, XGBoost, Tensorflow, PyTorch, MXNet, LLM) Qualifications Required: Bachelor's Degree with 7 years experience; Master's Degree with 6 years experience; PhD with 2 years experience. More ❯

unstructured data eg. Text, PDFs, jpgs, call recordings, video, etc. Knowledge of machine learning modelling techniques and how to fine-tune those models eg. XGBoost, Deep Neural Networks, Transformers, Markov chains, etc. Experience using specialized machine learning libraries e.g. Fastai, Keras, Tensorflow, pytorch, sci-kit learn, huggingface, etc. Must demonstrate More ❯

unstructured data eg. Text, PDFs, jpgs, call recordings, video, etc. Knowledge of machine learning modelling techniques and how to fine-tune those models eg. XGBoost, Deep Neural Networks, Transformers, Markov chains, etc. Experience using specialized machine learning libraries e.g. Fastai, Keras, Tensorflow, pytorch, sci-kit learn, huggingface, etc. Must demonstrate More ❯

unstructured data eg. Text, PDFs, jpgs, call recordings, video, etc. Knowledge of machine learning modelling techniques and how to fine-tune those models eg. XGBoost, Deep Neural Networks, Transformers, Markov chains, etc. Experience using specialized machine learning libraries e.g. Fastai, Keras, Tensorflow, pytorch, sci-kit learn, huggingface, etc. Must demonstrate More ❯

unstructured data eg. Text, PDFs, jpgs, call recordings, video, etc. Knowledge of machine learning modelling techniques and how to fine-tune those models eg. XGBoost, Deep Neural Networks, Transformers, Markov chains, etc. Experience using specialized machine learning libraries e.g. Fastai, Keras, Tensorflow, pytorch, sci-kit learn, huggingface, etc. Must demonstrate More ❯

years technical experience. Relevant experience may be accepted in place of a degree Experience with various machine learning libraries (i.e. Apache Spark, Scikit-learn, XGBoost, etc.) Experience with various data manipulation and pipeline libraries (i.e. Pandas, Polars, matplotlib, Plotly, numpy, scipy, etc.)Experience with data science environments (e.g. Jupyter Notebook More ❯

looking for: Essential: 5+ years of proven experience delivering AI/ML models in production environments. Advanced knowledge of machine learning, deep learning (e.g., XGBoost, LSTMs, transformers), and statistical modeling. Proficient in Python and machine learning libraries such as Scikit-learn, TensorFlow, PyTorch, etc. Hands-on experience with MLOps tools More ❯

looking for: Essential: 5+ years of proven experience delivering AI/ML models in production environments. Advanced knowledge of machine learning, deep learning (e.g., XGBoost, LSTMs, transformers), and statistical modeling. Proficient in Python and machine learning libraries such as Scikit-learn, TensorFlow, PyTorch, etc. Hands-on experience with MLOps tools More ❯

looking for: Essential: 5+ years of proven experience delivering AI/ML models in production environments. Advanced knowledge of machine learning, deep learning (e.g., XGBoost, LSTMs, transformers), and statistical modeling. Proficient in Python and machine learning libraries such as Scikit-learn, TensorFlow, PyTorch, etc. Hands-on experience with MLOps tools More ❯

to the 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 More ❯

the organisation. Required Skills & Experience: Extensive experience conducting data analysis within relevant sectors. Proficiency in SQL, Python, and data science libraries such as sklearn, XGBoost, and CatBoost. Experience with Azure, MLOps, and API frameworks. Strong understanding of statistical methods, probability theory, pricing optimisation, and elasticity modelling. Expertise with data visualisation More ❯

the organisation. Required Skills & Experience: Extensive experience conducting data analysis within relevant sectors. Proficiency in SQL, Python, and data science libraries such as sklearn, XGBoost, and CatBoost. Experience with Azure, MLOps, and API frameworks. Strong understanding of statistical methods, probability theory, pricing optimisation, and elasticity modelling. Expertise with data visualisation More ❯

time-series forecasting, clustering , and other core ML techniques. Strong experience with SQL and querying large, complex datasets. Proficiency in Python (Pandas, scikit-learn, XGBoost, etc.); familiarity with R or dbt is a plus. Experience working with BI tools such as Looker, Tableau, or Power BI. Comfort working in high More ❯

time-series forecasting, clustering , and other core ML techniques. Strong experience with SQL and querying large, complex datasets. Proficiency in Python (Pandas, scikit-learn, XGBoost, etc.); familiarity with R or dbt is a plus. Experience working with BI tools such as Looker, Tableau, or Power BI. Comfort working in high More ❯

time-series forecasting, clustering , and other core ML techniques. Strong experience with SQL and querying large, complex datasets. Proficiency in Python (Pandas, scikit-learn, XGBoost, etc.); familiarity with R or dbt is a plus. Experience working with BI tools such as Looker, Tableau, or Power BI. Comfort working in high More ❯

Familiarity with other cloud platforms, such as AWS or Google Cloud Platform, though Azure is the primary environment. Experience with neural networks, TensorFlow, CatBoost, XGBoost, SKlearn, or Pandas. Exposure to Terraform or Infrastructure as Code (IaC), with a willingness to engage with these tools as needed. A graduate or postgraduate More ❯

trees, and other traditional machine learning models, translating conceptual ideas into actual solutions. Fluent in some of these machine learning frameworks such as SKLearn, XGBoost, PyTorch, or Tensorflow. Proficient in Python and able to transform abstract machine learning concepts into robust, efficient, and scalable solutions. Strong Computer Science fundamentals and More ❯

science or machine learning role; startup experience preferred. Strong coding skills in Python (and/or R); deep familiarity with libraries like scikit-learn, XGBoost, PyTorch, TensorFlow . Strong grasp of probability theory, statistical inference, and A/B testing . Experience with causal inference and online learning methodologies. Proficiency More ❯

with Transformer models Familiarity with PyTorch, ideally Hugging Face models Experience using Docker Technologies Utilized Python Python packages: pandas, numpy, scikit-learn, medspaCy, nltk, XGBoost, PyTorch Cloud: GCP Git/gitlab Docker PostgreSQL, MySQL Transformers Streamlit Azra AI Values At Azra AI, we value trust, integrity, honesty, transparency, innovation, transformation More ❯

fresh ideas to the table What we’re looking for: Strong Python skills and experience in ML libraries like scikit-learn, PyTorch, TensorFlow , or XGBoost Hands-on experience building and deploying ML models into production environments Familiarity with ML Ops workflows (e.g., MLflow, Airflow, Weights & Biases, or Kubeflow) Experience working More ❯

fresh ideas to the table What we’re looking for: Strong Python skills and experience in ML libraries like scikit-learn, PyTorch, TensorFlow , or XGBoost Hands-on experience building and deploying ML models into production environments Familiarity with ML Ops workflows (e.g., MLflow, Airflow, Weights & Biases, or Kubeflow) Experience working More ❯

fresh ideas to the table What we’re looking for: Strong Python skills and experience in ML libraries like scikit-learn, PyTorch, TensorFlow , or XGBoost Hands-on experience building and deploying ML models into production environments Familiarity with ML Ops workflows (e.g., MLflow, Airflow, Weights & Biases, or Kubeflow) Experience working More ❯