Senior Technical Lead - Traditional ML

This role is accountable for developing, optimizing, and deploying advanced machine learning and natural language processing solutions focused on time series forecasting. The individual applies solid expertise in Python, distributed data processing, and ML model evaluation to deliver complex predictive models, ensuring technical excellence and successful project outcomes within the development team.

• Develop and implement time series forecasting models using Python, scikit-learn, Tensor Flow, and Stats Models, optimizing for accuracy and scalability.
• Integrate and process large-scale streaming data with Apache Kafka and Spark, enabling real-time model training and inference.
• Evaluate machine learning models using cross-validation, ROC/AUC, Precision/Recall, F1-score, and confusion matrix to ensure robust predictive performance.
• Apply advanced NLP techniques with NLTK and Spa Cy to extract and preprocess relevant features for forecasting tasks.
• Optimize model deployment pipelines using Apache Airflow and Hadoop, ensuring efficient workflow orchestration and data management.
• Collaborate within the development team to troubleshoot, refine, and enhance ML solutions, ensuring adherence to best practices and coding standards.

• Advanced proficiency in machine learning and natural language processing, with solid experience in time series analysis and forecasting.
• Strong skills in Python programming, including Numpy, Pandas, Scikit-learn, Tensor Flow, PyTorch, XGBoost, and LightGBM.
• In-depth knowledge of distributed data processing with Apache Spark and real-time data integration using Apache Kafka.
• Solid understanding of ML model evaluation metrics and techniques, including cross-validation and performance optimization.
• Experience with workflow orchestration tools such as Apache Airflow and big data platforms like Hadoop.
• Advanced proficiency in NLP libraries including NLTK and Spa Cy.

• Optional but valuable: certifications such as Tensor Flow Developer Certificate or AWS Certified Machine Learning.

A candidate’s pay within the range will depend on their skills, experience, education, and other factors permitted by law. This role may also be eligible for performance-based bonuses subject to company policies. In addition, this role is eligible for the following benefits subject to company policies: medical, dental, vision, pharmacy, life, accidental death & dismemberment, and disability insurance; employee assistance program;

401(k) retirement plan; 10 days of paid time off per year (some positions are eligible for need-based leave with no designated number of leave days per year); and 10 paid holidays per year.