ML OPS Engineer
Apply NowCompany: RICEFW Technologies, Inc.
Location: Orlando, FL 32828
Description:
Role: ML OPS Engineer
Location: Orlando, FL (Onsite)
Duration: 6+ months
Full Time
Experience Required:
Responsibilities:
Requirements:
Location: Orlando, FL (Onsite)
Duration: 6+ months
Full Time
Experience Required:
- Overall 10 years out of 5-8 years relevant experience in MLOps.
- 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