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Please Turn on your JavaScript

Epicareer might not working properly because your browser javascript is turned off.

What is JavaScript?

JavaScript is like the magic behind making websites interactive. Basically, it makes Epicareer more enjoyable and engaging.
How do i turn this on?
Find tutorial for your browser below :
  1. Make sure the webpage is open.
  2. In the Safari app on your Mac, choose Safari > Preferences, then click Security.
  3. Make sure the Enable JavaScript checkbox is selected.
  4. Click Websites.
  5. On the left, click Content Blockers.
  6. Make sure Off is chosen in the pop-up menu next to the website.
  7. On the left, click Pop-up Windows.
  8. Make sure Allow is chosen in the pop-up menu next to the website.
Visit Site here
  1. Open Chrome on your computer.
  2. Click. then Settings.
  3. Click Privacy and Security.
  4. Click Site settings.
  5. Click JavaScript.
  6. Select Sites can use Javascript.
Visit Site here
  1. If you're running Windows OS, in the Firefox window, click Tools > Options.
  2. Tip: If you're running Mac OS, click the Firefox drop-down list > Preferences.
  3. On the Content tab, click the Enable JavaScript check box.
Visit Site here
  1. Click the "Settings and more" icon at the top right of the Edge browser window.
  2. Click Settings.
  3. From the Settings menu, click Cookies and site permissions.
  4. Scroll down and click on JavaScript.
  5. In the JavaScript window, toggle the slider to "on" or "allowed."
  6. Close the Settings tab.
  7. Refresh the page.
Visit Site here
  1. Go to Settings.
  2. Click Advanced in the left sidebar, and click Privacy & security.
  3. Under Privacy and security, click Site settings.
  4. Click JavaScript.
  5. At the top, turn on or off Allowed (recommended).
Visit Site here
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Jobs or company...

Machine Learning Engineer

Salary undisclosed
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We are seeking an experienced Machine Learning Engineer with a strong background in the AWS ecosystem and proficiency in building front-end applications using AWS tools like AWS Amplify. The ideal candidate will have hands-on experience working with large datasets, developing ETL pipelines, and rapidly rolling out cutting-edge ML/AI prototypes. This role combines expertise in machine learning, cloud technologies, and user-friendly interfaces to deliver innovative, scalable solutions.

Responsibilities

Design, develop, and deploy machine learning models and workflows using AWS services such as SageMaker, Lambda, Glue, and Step Functions.

Build and maintain ETL pipelines using AWS Glue, Athena, S3, and related services to process large volumes of structured and unstructured data.

Rapidly develop and deploy ML/AI prototypes and proof-of-concept applications to address evolving business needs.

Create and manage front-end applications using AWS Amplify, integrating with backend services like API Gateway, AppSync, and DynamoDB.

Optimize ML models and data pipelines for performance, scalability, and cost-efficiency on AWS infrastructure.

Collaborate with data engineers, scientists, and business teams to gather requirements and translate them into practical machine-learning solutions.

Monitor and troubleshoot deployed models and data workflows using tools like Amazon CloudWatch and SageMaker Model Monitor.

Ensure security, scalability, and compliance of data and applications in alignment with AWS best practices.

Requirements

Bachelor’s or Master’s degree in Computer Science, Data Science, Machine Learning, or a related field.

4-6 years of experience in machine learning and AWS cloud technologies.

Proficiency in building ETL pipelines and handling large datasets in a cloud environment.

Hands-on experience with AWS SageMaker for model training, deployment, and optimization.

Strong expertise in AWS Amplify for front-end application development.

Demonstrated experience in rapidly prototyping and deploying cutting-edge ML/AI applications.

We are seeking an experienced Machine Learning Engineer with a strong background in the AWS ecosystem and proficiency in building front-end applications using AWS tools like AWS Amplify. The ideal candidate will have hands-on experience working with large datasets, developing ETL pipelines, and rapidly rolling out cutting-edge ML/AI prototypes. This role combines expertise in machine learning, cloud technologies, and user-friendly interfaces to deliver innovative, scalable solutions.

Responsibilities

● Design, develop, and deploy machine learning models and workflows using AWS services such as SageMaker, Lambda, Glue, and Step Functions.

● Build and maintain ETL pipelines using AWS Glue, Athena, S3, and related services to process large volumes of structured and unstructured data.

● Rapidly develop and deploy ML/AI prototypes and proof-of-concept applications to address evolving business needs.

● Create and manage front-end applications using AWS Amplify, integrating with backend services like API Gateway, AppSync, and DynamoDB.

● Optimize ML models and data pipelines for performance, scalability, and cost-efficiency on AWS infrastructure.

● Collaborate with data engineers, scientists, and business teams to gather requirements and translate them into practical machine-learning solutions.

● Monitor and troubleshoot deployed models and data workflows using tools like Amazon CloudWatch and SageMaker Model Monitor.

● Ensure security, scalability, and compliance of data and applications in alignment with AWS best practices.

Requirements

● Bachelor’s or Master’s degree in Computer Science, Data Science, Machine Learning, or a related field.

● 4-6 years of experience in machine learning and AWS cloud technologies.

● Proficiency in building ETL pipelines and handling large datasets in a cloud environment.

● Hands-on experience with AWS SageMaker for model training, deployment, and optimization.

● Strong expertise in AWS Amplify for front-end application development.

● Demonstrated experience in rapidly prototyping and deploying cutting-edge ML/AI applications.