Software Engineer, Machine Learning Operations

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About this kind of role

What a Software Engineer, Machine Learning Operations usually does. The employer's own details are in the listing.

Typically does: A Machine Learning Operations (MLOps) Software Engineer focuses on automating and streamlining the machine learning lifecycle, from model development to deployment and monitoring. This involves building and maintaining infrastructure, pipelines, and tools to support data scientists and machine learning engineers. They ensure models are reliable, scalable, and performant in production environments, often collaborating closely with other engineering teams. Responsibilities frequently include troubleshooting issues and improving the efficiency of machine learning workflows.

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

Good fit for: Individuals with a strong software engineering background and a passion for applying their skills to solve complex machine learning challenges thrive in this role.