Machine Learning Work From Home Internship

Selected intern's day-to-day responsibilities include:

1. Sourcing collecting and preprocessing large-scale datasets required for training machine learning models ensuring data quality consistency and relevancy through cleaning augmentation and validation and collaborating with domain experts to understand data requirements and annotations
2. Designing implementing and training machine learning models including computer vision NLP models and large language models fine-tuning pre-trained models for domain-specific tasks using transfer learning techniques and experimenting with different architectures and hyperparameters to improve model accuracy and performance
3. Establishing baseline performance for models through evaluation metrics conducting testing cross-validation and comparisons against state-of-the-art techniques and optimizing models for efficiency and scalability in real-world applications
4. Implementing end-to-end MLOps pipelines for deploying machine learning models in production environments automating workflows for model retraining monitoring and CI/CD pipelines ensuring model versioning reproducibility and scalability and collaborating with DevOps and software engineering teams to integrate models into existing systems
5. Developing APIs to expose machine learning models for external consumption designing efficient and scalable endpoints to serve predictions and integrating APIs with frontend or client applications for real-time or batch processing
6. Deploying machine learning models to production environments using cloud services or containerized platforms ensuring models are optimized for low-latency inference and monitoring deployed models tracking performance metrics and setting up alerts for model degradation or drift

2