Software Engineer - AI Tooling Infrastructure

About this kind of role

What a Software Engineer - AI Tooling Infrastructure usually does. The employer's own details are in the listing.

Typically does: Designs, develops, tests, and maintains infrastructure and tools that support artificial intelligence and machine learning development. This includes building pipelines for data processing, model training, and deployment, as well as creating tools to improve developer productivity. Responsibilities often involve ensuring scalability, reliability, and security of AI systems. Collaboration with data scientists and machine learning engineers is a common aspect of the role.

Tools and skills: Proficiency in programming languages like Python, Java, or Go, experience with cloud platforms (AWS, Azure, or Google Cloud), and familiarity with DevOps practices, containerization (Docker, Kubernetes), and version control systems (Git) are generally required.

Good fit for: Individuals with a strong background in software engineering and a keen interest in the practical challenges of building and scaling AI solutions often thrive in this role.