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To ensure you’re set up for success, you will bring the following skillset & experience:
You have experience in AI and NLP techniques with expertise in deep learning and natural language processing.
You have 3+ years of experience working in a Data Science/Machine Learning Engineering role in MLOps or DevOps.
You have the Ability to design and implement cloud solutions and ability to build MLOps pipelines on cloud solutions (OCP, AWS, MS Azure or GCP)
You have experience with MLOps Frameworks like Kubeflow, MLFlow, DataRobot, Airflow etc., experience with Docker and Kubernetes, OpenShift
You have experience with containerization technologies (e.g., Docker) and orchestration tools (e.g., Kubernetes).
You have experience in Programming languages like Python, Go, Ruby or Bash, good understanding of Linux, knowledge of frameworks such as scikit-learn, Keras, PyTorch, Tensorflow, etc.
You have Ability to understand tools used by data scientist and experience with software development and test automation.
You can Execute AI models and algorithms in the production scenario to elevate scalability and performance.
You have Familiarity with cloud platforms such as AWS, OCP, GCP, or Azure.
You have experience with version control systems such as Git.
CI/CD (Jenkins) environment with popular DevOps tools
Experience with Agile methodology, use of Atlassian products Jira, Confluence )
You are familiar and can take advantage of advanced IDEs such as IntelliJ, Eclipse or VSCode .
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