Software Engineer - Model Performance Systems

About this kind of role

What a Software Engineer - Model Performance Systems usually does. The employer's own details are in the listing.

Typically does: Develops and maintains systems that evaluate and monitor the performance of machine learning models. This includes designing automated testing frameworks, building dashboards to visualize model metrics, and implementing pipelines for retraining and redeployment. The role often involves collaborating with machine learning engineers and data scientists to identify and address performance bottlenecks. Responsibilities may also extend to ensuring the reliability and scalability of model performance infrastructure.

Tools and skills: Proficiency in programming languages like Python, experience with cloud platforms (e.g., AWS, Azure, GCP), familiarity with machine learning frameworks (e.g., TensorFlow, PyTorch), and knowledge of data visualization tools are generally required.

Good fit for: Individuals with a strong analytical background and a passion for building robust, scalable systems that support machine learning workflows typically thrive in this role.