Sr. Software Development Engineer, ML Infrastructure Team

About this kind of role

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

Typically does: Designs, develops, tests, and maintains machine learning infrastructure components. This includes building and scaling data pipelines, model deployment systems, and monitoring tools. Responsibilities often involve optimizing performance, ensuring reliability, and automating processes within the machine learning lifecycle. Collaboration with data scientists and machine learning engineers is a key aspect of the role.

Tools and skills: Proficiency in programming languages like Python and Java, experience with cloud platforms (e.g., AWS, Azure, GCP), and familiarity with big data technologies (e.g., Spark, Hadoop) are generally required, alongside knowledge of DevOps practices and containerization technologies like Docker and Kubernetes.

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