Lead Engineer- ML QA

Key Skills

Analytical and Problem solving, AWS, Azure, Confluence, Continuous Integration & Continuous Delivery - CI/CD, Docker, Effective communication skills, GitLab, Google Cloud Platform (GCP), Grafana, Java Programming, Jenkins, JIRA, Kibana, Kubernetes-K8s, Leadership Skill, Machine learning techniques, MongoDB, MySQL, PostgreSQL, Python Programming, SQL

Job Description

We are seeking an experienced and highly motivated QA Lead to oversee the quality assurance for our machine learning products and services. The ideal candidate will have a deep understanding of machine learning technologies, along with a strong hands-on experience in quality assurance and different methodologies.

Responsibilities

- Lead and mentor a team of QA engineers to ensure the highest quality product delivery.

- Design, implement, and oversee the overall QA strategy for machine learning-based products and services.

- Collaborate closely with cross-functional teams, including software engineers, machine learning scientists, and product managers.

- Design and execute test plans, including manual and automated test cases.

- Monitor QA results and metrics, and report findings to senior management.

- Lead root cause analysis and complex problem-solving initiatives for project issues.

- Maintain up-to-date knowledge of the latest QA tools, frameworks, and best practices, and drive adoption across the QA team.

- Ensure compliance with industry and company quality standards.

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.

- In-depth experience with QA methodologies, tools, and processes.

- Understanding of machine learning products lifecycle.

- Strong experience with data quality assessment.

- Proven experience in writing clear, concise, and comprehensive test plans and test cases.

- Familiarity with software development lifecycle (SDLC) and agile methodologies.

- Experience with cloud-based services and architectures.

- Strong problem-solving skills and excellent attention to detail.

- Domain experience in health, finance or climate industry is a plus.

- Excellent verbal and written communication skills.

Programming languages: Python, Java, SQL

Testing Tools: Selenium, JUnit, PyTest, Gatling, Postman

CI/CD: Jenkins, GitLab CI/CD,

Version Control: Git

Cloud Services: Azure (optional AWS, GCP)

Databases: MySQL, MongoDB, PostgreSQL

Monitoring Tools: Grafana, Kibana

Collaboration: Jira, Confluence

Other Technologies: Docker, Kubernetes