As an Engineer - ML QA, you will develop and execute quality assurance processes to ensure the accuracy, reliability, and performance of machine learning models and AI applications. Reporting to the Lead Engineer - ML QA, you will collaborate with data scientists, software engineers, and product teams to validate ML models and systems, maintaining high standards of quality for the company's AI and machine learning initiatives.
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Your responsibilities will include:
- Designing and executing test plans, including manual and automated test cases.
- Collaborating with cross-functional teams to ensure robust and reliable ML models.
- Monitoring ML QA results and metrics, reporting findings to senior management.
- Leading root cause analysis and complex problem-solving initiatives for project issues.
- Maintaining knowledge of the latest QA tools, frameworks, and best practices.
Qualifications:
- Bachelor’s degree in Computer Science, Engineering, or a related technical field.
- Minimum of 5 years of experience in a QA role, with at least 2 years in a leadership position.
- Experience with QA methodologies, tools, and processes.
- Familiarity with software development lifecycle (SDLC) and agile methodologies.
- Excellent verbal and written communication skills.
Skills:
- Programming Languages: Python, Java, SQL
- Testing Tools: Playwright, Selenium, JUnit, PyTest, Gatling, Postman, RestAssured
- CI/CD: Jenkins, GitLab CI/CD
- Version Control: Git
- Cloud Services: Azure (optional AWS, GCP)
- Databases: MySQL, MongoDB, PostgreSQL
- Monitoring Tools: Grafana, Kibana
- Collaboration Tools: Jira, Confluence
- Other Technologies: Docker, Kubernetes
This role offers a chance to work in a diverse and inclusive environment, focusing on innovation and significant advancements in AI technology. If you possess a performance-driven mindset and are eager to create unique customer-centric solutions, we encourage you to apply.
Language Requirements: Proficient in English, additional language skills may be beneficial.
