Overview
On Site
$40 - $50
Contract - W2
Skills
Machine Learning (ML)
Amazon S3
Amazon Web Services
Amazon SageMaker
Communication
Data Analysis
Data Engineering
Data Processing
Data Science
Decision Support
Decision-making
Documentation
Extract
Transform
Load
Hosting
manufracutring
Job Details
JD
We are looking for a skilled AWS ML Engineer to join our team and contribute to building data-driven solutions that enhance decision-making, optimize operations, and deliver business insights.
In this role, you will leverage AWSs advanced data and machine learning services to analyze large datasets, build predictive models, and deploy scalable machine learning solutions.
The ideal candidate will have a solid background in statistical analysis, machine learning, and data science, along with hands-on experience with AWS tools for model deployment and data processing
Key Responsibilities:
Collaboration
Technical Skills:
We are looking for a skilled AWS ML Engineer to join our team and contribute to building data-driven solutions that enhance decision-making, optimize operations, and deliver business insights.
In this role, you will leverage AWSs advanced data and machine learning services to analyze large datasets, build predictive models, and deploy scalable machine learning solutions.
The ideal candidate will have a solid background in statistical analysis, machine learning, and data science, along with hands-on experience with AWS tools for model deployment and data processing
Key Responsibilities:
- Data Analysis and Exploration Analyze large, complex datasets to extract meaningful insights and identify trends.
- Perform exploratory data analysis (EDA) using AWS data processing tools.
- Model Development
- Build, train, and evaluate machine learning models using AWS services such as SageMaker, and frameworks like TensorFlow.
- ETL and Data Preparation
- Work with AWS Glue, Redshift, Textract and other data engineering tools to preprocess, transform, and manage data for machine learning purposes
- Machine Learning Pipeline Development
- Develop end-to-end machine learning pipelines on AWS to automate and operationalize the deployment of models at scale.
Collaboration
- Work closely with data engineers, business analysts, and stakeholders to understand business needs and tailor data science solutions to meet those needs.
- Model Deployment and Monitoring
- Deploy models to production and set up monitoring systems to track performance, accuracy, and other key metrics.
- Use SageMaker and Lambda for model hosting and API development.
- Documentation and Reporting Document models, processes, and findings for stakeholders, enabling clear communication of results and decision support.
Technical Skills:
- AWS Services Hands-on experience with AWS SageMaker, Textract, Comprehend, Lambda, Glue, Redshift, and S3.
- Machine Learning and Statistical Techniques Strong
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.