Description

You will design, build, and optimize machine learning models and data pipelines for production systems.

This role is on-site.

Responsibilities

• Develop and tune ML models using Python, including linear/logistic regression, decision trees, random forests, XGBoost, LightGBM, SVM, and KNN.
• Implement deep learning architectures such as CNNs, RNNs, LSTMs, and Transformers for NLP, computer vision, and time-series forecasting.
• Perform data preparation and query optimization using SQL, leveraging joins, window functions, CTEs, and advanced query techniques.
• Evaluate model performance using metrics like Precision, Recall, F1, ROC-AUC, MSE, and RMSE.
• Conduct hyperparameter tuning via grid search, randomized search, and cross-validation.

Required Skills

• 10+ years of hands-on software engineering experience.
• Strong proficiency in Python for data preprocessing and model implementation.
• Expert-level SQL skills, including query optimization and complex joins.
• Deep understanding of classical ML algorithms (Random Forest, XGBoost, LightGBM, SVM, KNN).
• Experience with deep learning frameworks (TensorFlow, Keras, PyTorch) and architectures (CNNs, RNNs, LSTMs, Transformers).
• Ability to apply ML to NLP, computer vision, and time-series use cases.
• Bachelor’s degree or equivalent graduate education.

Key Skills

Education

Any Gradute