Engineer - ML QA

Overview

As an Engineer - ML QA at Inception, you will be responsible for developing and executing 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 work closely with data scientists, software engineers, and product teams to validate ML models and systems. Your role is crucial in maintaining high standards of quality for the company's AI & machine learning initiatives.

The Engineer - ML QA is a technical role focused on testing and validating machine learning models to ensure they meet the required quality standards. This role involves creating and executing test plans, analyzing test results, test data preparation, and collaborating with various teams to ensure ML models are robust and reliable. The ideal candidate will have experience in quality assurance for machine learning projects and a solid understanding of ML techniques and tools.

Responsibilities

As an Engineer - ML QA, you will be responsible for executing QA processes for machine learning models to ensure they meet the company’s quality standards. Your role will encompass a range of activities focused on model validation, testing, and collaboration.

1. Collaborate with a team of ML QA engineers to ensure the highest quality product delivery.
2. Design, implement, and oversee the overall ML QA strategy for machine learning-based products and services.
3. Collaborate closely with cross-functional teams, including software engineers, machine learning scientists, and product managers.
4. Design and execute test plans, including manual and automated test cases.
5. Monitor ML QA results and metrics, and report findings to senior management.
6. Lead root cause analysis and complex problem-solving initiatives for project issues.
7. Maintain up-to-date knowledge of the latest QA tools, frameworks, and best practices, and drive adoption across the QA team.
8. Ensure compliance with industry and company quality standards.

Qualifications

Skills and attributes for success:

1. Bachelor’s degree in Computer Science, Engineering, or a related technical field.
2. Minimum of 5 years of experience in a QA role, with at least 2 years in a leadership position.
3. In-depth experience with QA methodologies, tools, and processes.
4. Understanding of machine learning products lifecycle.
5. Strong experience with data quality assessment.
6. Proven experience in writing clear, concise, and comprehensive test plans and test cases.
7. Familiarity with software development lifecycle (SDLC) and agile methodologies.
8. Experience with cloud-based services and architectures.
9. Strong problem-solving skills and excellent attention to detail.
10. Domain experience in health, finance or climate industry is a plus.
11. Excellent verbal and written communication skills.

Tech stack:

1. Programming languages: Python, Java, SQL
2. Testing Tools: Playwright, Selenium, JUnit, PyTest, Gatling, Postman, RestAssured
3. CI/CD: Jenkins, GitLab CI/CD
4. Version Control: Git
5. Cloud Services: Azure (optional AWS, GCP)
6. Databases: MySQL, MongoDB, PostgreSQL
7. Monitoring Tools: Grafana, Kibana
8. Collaboration: Jira, Confluence
9. Other Technologies: Docker, Kubernetes

What we look for

If you are a performance-driven, inquisitive mind with the agility to adapt to ambiguity, you will fit right in. You should be eager to explore opportunities to build meaningful collaborations with stakeholders and aspire to create unique customer-centric solutions. Bias for action and a passion to conquer new frontiers in the AI space is at the heart of the Inception community.

What working at Inception offers

Culture: An open, diverse and inclusive environment with a global vision that encourages personal growth and focuses on ground-breaking, industry-first innovations.

Career: Outstanding learning, development & growth opportunities via structured training programs and innovative, high-tech projects.

Work-Life: A hybrid work policy to strike the perfect balance between office and home.

Rewards: A competitive remuneration package with a host of perks including healthcare, education support, leave benefits and more.

If you can confidently demonstrate that you meet the criteria above, please contact us as soon as possible.