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 ML Pipelines
Experience working with distributed data processing using PySpark.
Solid understanding of software engineering principles and version control (e.g., Git).
Excellent problem-solving skills and ability to work independently or in a team.
Typically, 6+ years of relevant work experience in industry, with a minimum of 2+ years in a similar role.
Proficiencies in data cleansing, exploratory data analysis, and data visualization
Continuous learner that stays abreast with industry knowledge and technology
