Machine Learning Engineer (CAN)

What You’ll Do

• Work with cross-functional teams to gather and analyze data requirements
• Develop and implement machine learning models for structured data
• Perform data pre-processing, feature engineering, and model selection
• Evaluate and improve model performance using various metrics
• Collaborate with software engineers to integrate machine learning models into production systems
• Monitor and maintain machine learning models in a production environment
• Keep up-to-date with the latest advancements in machine learning and AI
• Author and publish the novelty of the works accomplished in peer reviewed journals and conferences.

Knowledge, Skills & Abilities

• Experience in NLP and any of the deep learning frameworks such as TensorFlow, Keras, PyTorch, etc
• Proficiency with modern statistical modeling (regression, boosting trees, random forests, etc.) including classification, regression, and clustering models
• Strong experience in Python and its libraries for data analysis and machine learning (such as NumPy, Pandas, Scikit-learn, etc.)
• Data Analysis Libraries: Pandas, PySpark, Numpy, Matplotlib
• Advanced analytical skills, including time-series forecasting
• Knowledge of SQL and working with relational databases
• Strong problem-solving and analytical skills
• Excellent communication skills and the ability to work in a team environment

Education and Work Experience

• Bachelor's or Master's degree or Phd in Computer Science, Mathematics, or a related field
• 3+ years of experience in building and deploying machine learning models for structured data

Plus to have

Prior experience in working with synthetic data

Research and publication experience