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.
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.
