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Principal AI/ML Engineer
Career Insights for Machine Learning Engineer
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Based on Virginia data
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What they do
A Machine Learning Engineer specializes in designing, building, and deploying machine learning models. They utilize statistical and mathematical techniques, parallelizing processing, hyperparameter tuning, and other optimization methodologies to improve model performance. Responsibilities also include collecting and preprocessing large datasets, conducting exploratory data analysis, working closely with data engineers to understand data requirements, and engineer input variables for machine learning models.
$123,933 / year median in Virginia
Job Description
Responsiblities:
Lead an agile technical team developing AI/ML and Business Intelligence solutions. Business Analysis & Project Support- requirements elicitation, process mapping, gap analysis, user story development, risk/issue/dependency tracking Business Transformation
- use-case documentation, data sensitivity/compliance assessments, stakeholder interviews, change management Systems & Technology Analysis
- architecture/dependency mapping, integration analysis, configuration management, workflow diagnostics AI/ML Testing, Validation & Documentation
- test plan execution, model inventories, model cards, explainability artifacts, drift/anomaly monitoring, AI governance documentation Solution Design & Development
- translating requirements into technical specs, workflow automation builds, data transformation design.
Technology Stack:
Required Amazon Sagemaker, Python, Amazon SageMaker Studio Microsoft Power Automate, Power BI DBeaver JIRA, GitHub, ServiceNow Preferred SharePoint Online Education, Experience and Skills:
Required Bachelor's degree in computer science or a related field Minimum 5 years of hands-on experience designing, implementing and maintaining AI/ML models out of which at least 2 years with AWS Sagemaker. Hands-on experience with Python and Machine learning libraries such as TensorFlow and Keras. Experience with data analysis, data cleansing techniques, feature engineering, model design, model validation, with good understanding of model metrics Experience with one or more of the following types of models- Linear regression, Logistic regression, Time series analysis and forecasting At least 5 years of experience as a hands-on lead developer, developing code and managing projects using required technology stack (see below).