RIT Solutions, Inc.
Posted 69 days agoVerified live 5d ago
Machine Learning Engineer
Brief overview
Remote
Neural networksNatural Language ProcessingPythonMicrosoft AzurePyTorchTensorFlowRSQLDevOpsMLOpsCI/CD pipelinesAzure Machine LearningAzure DevOpsAzure DatabricksAzure FunctionsModel deploymentModel monitoring
About the company
RIT Solutions, Inc.ritsolinc.com
Jobdiva Job Portal: https://www1.jobdiva.com/candidates/myjobs/searchjobsdone.jsp?a=xbjdnwgjodtga1y1im2g881fkkeiwd0775lbvq8yqgps8vb2q36w2vj1ga6xxork&compid=-1 Recruitment (contingency search and campus selection).
Job description
Summary
RIT Solutions, Inc. is seeking a Machine Learning Engineer focused on developing, deploying, and optimizing machine learning models for enterprise applications. The ideal candidate will have hands-on experience with machine learning algorithms, neural networks, NLP, and Microsoft Azure.
Responsibilities
- Developing, deploying, and optimizing machine learning models for enterprise applications
- Building and supporting deployment/management in a production environment
- Selecting the right algorithms, preparing and analyzing data, training models, evaluating performance, and deploying models into cloud-based environments
Skills
- Neural networks
- NLP
- Python
- R
- SQL
- TensorFlow
- Keras
- PyTorch
- Microsoft Azure cloud platform
- DevOps and/or MLOps practices
- Model development, deployment, optimization, and lifecycle management
- Hands-on experience with supervised and/or unsupervised machine learning algorithms
- Experience building and deploying machine learning models from end to end
- Understanding of MLOps concepts such as CI/CD for ML models, version control, monitoring, automation, model retraining, and production support
Qualifications
Must Haves
- Neural networks
- NLP
- Python
- R
- SQL
- TensorFlow
- Keras
- PyTorch
- Microsoft Azure cloud platform
- DevOps and/or MLOps practices
- Model development, deployment, optimization, and lifecycle management
- Hands-on experience with supervised and/or unsupervised machine learning algorithms
- Experience building and deploying machine learning models from end to end
- Understanding of MLOps concepts such as CI/CD for ML models, version control, monitoring, automation, model retraining, and production support
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