Senior Software Engineer, ML Infrastructure

About this kind of role

What a Senior Software Engineer, ML Infrastructure usually does. The employer's own details are in the listing.

Typically does: Designs, builds, and maintains the infrastructure that supports machine learning models, including data pipelines, model training environments, and deployment systems. This role involves collaborating with machine learning scientists and engineers to optimize model performance and scalability. Responsibilities often include automating processes, monitoring system health, and ensuring data security and integrity. Focus is on creating robust and efficient systems for the entire machine learning lifecycle.

Tools and skills: Proficiency in cloud platforms (e.g., AWS, Azure, GCP), containerization technologies (e.g., Docker, Kubernetes), programming languages like Python and Java, and experience with big data processing frameworks (e.g., Spark, Hadoop) is generally expected.

Good fit for: Individuals with a strong background in software engineering and a passion for machine learning are typically successful in this role.