Data Engineer Machine Learning

NO H1, Sponsorship, or Sub-Tiers.

Only US Citizen, GC, GC-EAD, H4, and TN or OPT

• Machine Learning engineer has unique skills to build, code, apply correct algorithm and open-source libraries to create a ML model that best fits to the use case data set and the features applicable, test it, deploy it on the cloud hyperscaler using DevOps toolchain and infuse it in the process.
• ML engineer skills should not be confused with Data Scientist skills.

• Regression Models: Linear, RandomForest,XGBoost
• Classification Models: Kneighbors, RandomForest,XGBoost,SVM, Decision Trees
• Clustering Models: Kmeans, DBScan
• DeepLearning Models: Feature engineering
• Machine learning libraries: scikit-learn, spaCy, OpenCv, Pytorch
• ML Coding Language: python
• ML Tools: Notebooks, CLI Interfaces, Watson Studio, Azure ML Studio
• Test and Train the Model with Data
• Deploy and Register the Model
• Operationalize the Model: MLOps, AIOps, Rest WebService
• Data Pipeline Integration