Responsibilities
- Lead development of small to medium-scale machine learning components from design through deployment
- Convert technical specifications into clean, scalable, and well-tested code delivered on schedule
- Develop and manage data pipelines and feature engineering processes that power AI and ML applications
- Independently design, train, assess, and improve machine learning models using rigorous statistical and engineering methods
- Deploy machine learning models into production using microservices, APIs, batch processing, or real-time streaming
- Assist in defining and implementing monitoring systems for model performance, data drift, anomalies, and retraining needs
- Work closely with data engineers, software developers, data scientists, product managers, and business teams to meet project goals
- Gain strong understanding of system architecture, data structures, and technical documentation to inform implementation choices
- Adhere consistently to standards for code quality, documentation, version control, and governance policies
- Demonstrate adaptability and initiative in supporting team members with daily tasks and project demands
- Clearly communicate technical progress, design choices, and results to both technical and non-technical stakeholders
