Role: QA Engineer – Product Testing & Dataset Benchmarking

Exp: 6 Months to 2 Years

Work Mode: Work from Office, Mohali, PB

Shift time: Afternoon shift

Job Role & Responsibilities:

We are hiring a QA Engineer – Product Testing & Dataset Benchmarking to evaluate the quality, accuracy, and functionality of our AI-powered recruitment products.

This role is similar to a Manual QA role, but the primary focus will be on:

• Testing product functionalities using different datasets and real-world scenarios.
• Preparing, organizing, and maintaining datasets for product validation and benchmarking.
• Performing document testing across various file formats (PDF, DOC, DOCX, RTF, TXT, etc.) to validate product behavior and extraction accuracy.
• Evaluating Resume Parsing accuracy across multiple resume formats, layouts, and industries.
• Evaluating Job Description (JD) Parsing accuracy using diverse JD datasets.
• Testing Search & Match functionality and validating the relevance and accuracy of matching results.
• Comparing expected versus actual product outputs and identifying accuracy gaps.
• Preparing benchmarking and accuracy reports with detailed observations and metrics.
• Identifying, documenting, and reporting functional issues using tools such as JIRA.
• Re-testing fixes and tracking product accuracy improvements across releases.

Good to Have:

• Exposure to Manual QA methodologies.
• Experience creating test cases or test plans.
• Basic SQL and API testing knowledge.

• Experience with QA or issue-tracking tools such as JIRA, TestRail, or Zephyr.

  Qualification Required :

• Bachelor's degree in Computer Science, Information Technology, Engineering, Data Science, or a related field.
• 6 months – 2 years of experience in Product Testing, Manual QA, Software Testing, Data Validation, or a similar analytical role.
• Strong analytical and problem-solving skills with excellent attention to detail.
• Good written and verbal communication skills.
• Ability to analyze product outputs and document observations clearly.

Technical background:

Basic understanding of software testing principles and product validation.

Experience working with structured and unstructured datasets.

Comfortable testing documents in multiple formats such as PDF, DOC, DOCX, RTF, TXT, etc.

Basic knowledge of issue tracking tools such as JIRA or similar platforms.

Proficient in Microsoft Excel or Google Sheets for preparing benchmarking and analysis reports.

Understanding of AI/ML-based products or data-driven applications will be an advantage.

Minimum skills we look for:

Strong analytical and observation skills.

Product functionality testing.

Dataset preparation and validation.

Document testing across multiple file formats.

Benchmarking product accuracy using different datasets.

Ability to compare expected vs. actual product outputs.

Issue identification, reporting, and validation.

Good reporting and documentation skills.

Ability to work independently and collaboratively with Product and Engineering teams.