The Data Scientist / ML Engineer will demonstrate excellent knowledge of ML algorithms (e.g., Linear Regression, Logistic Regression, Clustering/Segmentation, Decision Tree, Random Forest, GBM, DNN, Naive Bayes, Support Vector Machine, etc.) to lead efforts, teams, projects, and engage with customer
- Design, implement, and optimize machine learning models (supervised, unsupervised, and reinforcement learning)
- Work on projects involving NLP, computer vision, recommendation systems, and predictive analytics
- Perform feature engineering, data preprocessing, and model selection
- Collaborate with Data Engineers to acquire and preprocess large datasets
- Build and maintain data pipelines to support model training, testing, and deployment
- Ensure data quality, consistency, and reliability
- Deploy ML models into production environments using CI/CD and MLOps practices
- Monitor model performance, retrain models, and manage model versioning
- Optimize inference performance and resource utilization
- Stay current with emerging ML/AI technologies, frameworks, and research
- Evaluate new algorithms, tools, and libraries to improve model performance
- Experiment with novel approaches to solve complex business problems
- Work with software engineers, data scientists, and product managers to integrate ML solutions into applications
Mentor junior engineers and share best practices in ML development and deployment
