Model Development: Design, build, and deploy end-to-end machine learning pipelines using Python and deep learning frameworks like TensorFlow or PyTorch .
Time-Series Excellence: Develop advanced forecasting models (e.g., LSTMs, Transformers, Prophet, or Arima-based hybrids) to solve complex temporal data challenges.
Productionalization: Optimize ML models for performance and scalability in production environments, including CI/CD integration and monitoring.
Leadership & Collaboration: Mentor junior engineers and collaborate with stakeholders to translate business requirements into technical AI solutions.
Technical Requirements
Experience: 5 - 7 years of professional experience in Machine Learning or Data Science, with a proven track record of deploying models to production.