Job Title: ML OPS Engineer
Location: Orlando, FL (Onsite)
Duration: 06+ Months
Send me the resumes to Venuelikatte@thetiltedge.com
Job Description –
Overall 10 years out of 5-8 years relevant experience in MLOps.
Azure + Terraform IAC, ML FLow and ML re-training pipelines
can support the team with deploying LLMs, ML inference APIs in Azure oor Databricks
Can deploy monitoring and full set of observability set.
Deep quantitative/programming background with a degree (Bachelor's) in a highly analytical discipline, like Statistics, Economics, Computer Science, Mathematics, Operations Research, etc
Responsibilities:
Design and implement cloud solutions, build MLOps on Azure cloud
Build CI/CD pipelines orchestration by Azure Devops or similar tools
Data science model review, code refactoring and optimization, containerization, deployment, versioning, and monitoring of its quality
Data science models testing, validation and tests automation
Communicate with a team of data scientists, data engineers and architect, document the processes.
Requirements:
Overall 10 years out of 5-8 years of experience in managing machine learning projects end-to-end, with the last 18 months focused on MLOps.
Monitoring Build & Production systems using automated monitoring and alarm tools
Knowledge of machine learning frameworks: TensorFlow, PyTorch, Keras, Scikit-Learn
Knowledge on building pipelines using synapse, databricks end to end.
Experience in API integration and data feeds with social analytics(Facebook, Instagram, Twitter).
Experience with MLOps tools such as ModelDB, Kubeflow, Pachyderm, and Data Version Control (DVC)
Experience in supporting model builds and model deployment for IDE-based models and autoML tools, experiment tracking, model management, version tracking & model training (Dataiku, Datarobot, Kubeflow, MLflow, neptune.ai) will be an addon, model hyperparameter optimization, model evaluation, and explainability (SHAP, Tensorboard)
Experience in Databricks, Azure DataLake Gen2 and Unity Catalog
Ability to understand tools used by data scientist and experience with software development and test automation
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