Responsibilities
- Construct and refine generative AI and large language model solutions, covering prompt design, model fine-tuning, and performance assessment.
- Create practical machine learning models to process extensive datasets, enabling classification, data enrichment, and automated workflows.
- Develop reliable data processing pipelines in Python, leveraging current ML libraries such as PyTorch, TensorFlow, and HuggingFace.
- Design scalable systems for ingesting, transforming, and managing data features efficiently.
- Operate and sustain machine learning systems in production, ensuring high availability, monitoring, and optimal performance.
- Work closely with interdisciplinary teams to define needs, assess model accuracy, and embed ML capabilities into live services.
- Implement effective strategies for managing model lifecycles, including version control, monitoring, periodic retraining, and economical deployment.
- Support engineering excellence through contributions to coding standards, peer reviews, and ongoing process enhancements.
Work Arrangement
Remote
