AI/ML Engineer
Tasks
- Add update scripts in automation suite
- Adhere to coding standards
- Automate tests for continuous improvement
- Build automation scripts
- Build test framework for quick feedback
- Collaborate with development and operations teams
- Define test data and reports
- Deprecate noisy irrelevant tests
- Develop acceptance tests for new components
- Examine build acceptance test results
- Execute and maintain automation test suite
- Execute scripts under load
- Experiment with environment sizing
- Generate test summary reports
- Improve portability and scalability of tests
- Investigate logs and troubleshoot issues
- Investigate performance and resource health
- Maintain automation framework
- Mentor less experienced resources
- Participate in production deployments
- Perform database testing
- Prioritize and resolve issues
- Raise and track defects
- Shift left with automation
- Translate manual test cases into automated tests
- Troubleshoot script and environment issues
- Use defect tracking tools
Perks/Benefits
- Career development opportunities
- Company-paid privacy certification exam fees
- Flexible PTO
- Healthcare coverage
- In-office collaboration opportunities
- Paid parental leave
- Retirement account support
Skills/Tech-stack
API Testing | Agile | Amazon Web Services | Azure | Bitbucket | CI/CD | Cause analysis | Cloud Platforms | Cloud platform | Confluence | Data Management | DevOps | Docker | Git | Google Cloud | Google Cloud Platform | JMeter | JUnit | Java | Jira | Kibana | Load Testing | Log Analysis | Mockito | NoSQL | Object-Oriented | Object-oriented programming | Performance Testing | Postman | REST | REST Assured | Root Cause Analysis | Root cause | SOAP | SQL | Selenium | TDD | Test Data | Test Data Management | Test automation | TestNG | Web Services
Education
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