You’ve operationalized machine learning while building scalable, robust, and secure products. A keen problem solver, use technology to work out complex analytical problems, and have:
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been exposed to different stages of machine learning system design and development
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utilized tools for machine learning pipeline management and monitoring (for example, MLflow, Pachyderm, Kubeflow, Seldon, Grafana)
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gained familiarity with automation and deployment (CircleCI/Jenkins/github actions, etc) and infrastructure as code (Terraform, CloudFormation, etc) technologies
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employed distributed processing frameworks such as Spark and Dask, and interacted with cloud platforms and container technologies
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gained practical knowledge of software engineering concepts and best practices, like testing frameworks, packaging, API design, DevOps, DataOps and MLOps
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developed excellent problem-solving skills and easily adapt to new technologies, trends, and frameworks
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gained an advanced degree in computer science, engineering, or mathematics, or have equivalent experience
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