Data Pipeline Development

Design, build, and maintain robust data pipelines specifically for product documentation systems

Implement ETL processes to extract valuable insights from technical documentation

Ensure data quality, integrity, and accessibility for AI model training and deployment

Machine Learning Implementation

Develop and deploy machine learning models to automate and enhance documentation workflows

Create intelligent classification and recommendation systems for technical content

Apply natural language processing techniques to improve documentation searchability and relevance

Technical Support & Integration

Provide specialized technical implementation support across AI initiatives

Collaborate with engineering teams to integrate AI solutions into existing systems

Troubleshoot complex data and model issues in production environments

Continuous Improvement

Monitor model performance and implement refinements based on feedback

Stay current with emerging AI and machine learning technologies

Contribute to best practices for AI implementation across the organization

Solid experience in data science, machine learning, or related field

Strong programming skills in Python and experience with data processing frameworks

Proven experience building and deploying machine learning models in production

Familiarity with NLP techniques and documentation systems

Experience with data pipeline development and management

Bachelor's degree in Computer Science, Data Science, Statistics, or related field

Experience with cloud-based ML platforms (AWS, Azure, GCP)

Knowledge of containerization and orchestration tools (Docker, Kubernetes)

Understanding of DevOps practices for ML workflows (MLOps)

Experience working with large document repositories or knowledge management systems

Familiarity with AI governance and responsible AI principles

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