Plano, TX, 75026, USA
22 hours ago
MLOps Engineer
Job Description · Exercise expertise in ideating and developing ML applications on prediction, recommendation, text analytics, computer vision, bots, and document intelligence. · Demonstrate deep knowledge of ML frameworks such as TensorFlow, PyTorch, Keras, Spacy, and scikit-learn. · Employ technical knowledge and hands-on experience with Azure ML Studio and Azure Kubernetes Service. · Experience in deploying Azure cloud services using Terraform templates with strong knowledge of DevOps principles and automated deployments. · Leverage advanced knowledge of Python open-source software stack such as Django or Flask, Django Rest or FastAPI, etc. · Work on model inferencing, validation and deployments to ensure models are deployed with the appropriate levels of validation and quality. · Create and maintain infrastructure to ingest, normalize, and combine datasets for actionable insights. We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to HR@insightglobal.com.To learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy: https://insightglobal.com/workforce-privacy-policy/. Skills and Requirements -8+ years relevant MLOps experience -Experience with MLOps Azure Kubernetes Argo, as well as Bento Azure ML Studio Model Inferencing
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