Quality Assurance (QA) Analyst

Quality Assurance (QA) Analyst – Job Description

Overview:

The QA Analyst will serve as a crucial pillar in maintaining and improving the integrity, robustness, and trustworthiness of the client’s AI detection platform. Working closely with the engineering, ML, and product teams, this person will validate core detection features, test new model versions, and ensure that detection outputs align with both technical and business requirements.

Core Responsibilities:

● Deepfake Detection Validation: Test the client’s GaussMass API (image and video) for correct classification of real vs synthetic media, including edge cases, adversarial examples, and novel deepfake generation techniques

● Functional & Regression Testing: Create and run test plans covering UI workflows (if applicable), API endpoint behaviors, error conditions, and model version updates

● Performance & Load Testing: Validate latency and throughput under realistic usage scenarios; ensure detection remains performant under scale

● Security / Robustness Testing: Work with engineering to test for potential adversarial inputs, malformed media, and attempts to bypass detection

● Documentation: Write detailed bug reports; document test cases, test coverage, and validation steps

● Continuous QA Process Improvement: Recommend areas for more rigorous testing, including automation or lightweight scripting (if needed) for recurrent test cases

● Release Validation: Participate in sprint planning and release cycles to certify test readiness, provide signoff, and coordinate with cross-functional teams before deployment

Key Deliverables:

● Test plans and test case suites tailored to the detection domain

● Bug logs with clear reproduction steps, severity assessment, and validation of fixes

● Release readiness reports summarizing test coverage, risk, and quality metrics

● Weekly or biweekly QA summaries (metrics, outstanding risks, test coverage) for the client’s product and engineering leaders

Ideal Traits & Skills – QA Analyst

Technical Skills:

● Solid understanding of manual QA methodologies

● Experience testing APIs (REST, potentially gRPC) — familiarity with tools like Postman is a plus

● Basic comfort with ML / AI concepts — able to understand detection output, model versioning, and data artifacts

● Experience in performance testing, load testing, or security testing is highly valuable

● Prior exposure to SaaS platforms, especially AI or media-intensive products, is preferred

Behavioral & Cognitive Traits:

● Extremely detail-oriented – must catch subtle discrepancies in detection output, edge-case failures, or model drift

● Strong documentation skills; able to communicate bug reports clearly and succinctly

● Analytical thinker — anticipates where things could break and aggressively tests those boundaries

● Collaborative — works well with remote / cross-functional teams (product, engineering, data science)

● Ownership mindset — treats QA as more than just “find bugs” but as a partnership in building a truly reliable product

Professional Attributes:

● High integrity and a security-first mindset. Given the nature of deepfake detection, sensitivity to data privacy and potential adversarial risk is critical

● Adaptability — The client’s roadmap involves rapid development (e.g., expanding from image to video to audio detection)

● Client-focused — as the client scales, QA issues may directly affect customers; being able to think from a client’s risk perspective matters

● Long-term commitment — willing to be a continuous partner, not a one-off contracto

Job Type: Full-time

Pay: Rs100,000.00 - Rs120,000.00 per month

Work Location: In person