About This Job
Zemoso Technologies
Location: Pune District, Maharashtra, India
Work Mode: On-site
Industry: IT Services and IT Consulting
Job Description
Job Description — QA Engineer (AI/ML & Analytics Testing)
Location: Mumbai / Pune
Experience: 3 – 6 Years
Role Type: Full Time Role
Overview
We are seeking a skilled QA Engineer with strong experience in analytics, data modeling, and Machine Learning (ML) solution testing. The role focuses on validating data accuracy, ML model outputs, data pipelines, and analytical applications to ensure high-quality, reliable, and scalable data-driven solutions. The ideal candidate will work closely with Data Engineers, Data Scientists, Product Teams, and Engineering stakeholders to define and execute comprehensive testing strategies across complex data and ML systems.
Key Responsibilities
Quality Engineering & Test Strategy
- Analyze product requirements and create detailed test plans, test cases, and validation strategies.
- Design, develop, and maintain automation frameworks, tools, and reusable test suites.
- Execute functional, integration, regression, performance, and end-to-end testing.
- Define testing strategies for AI/ML systems covering model validation, feature consistency, and acceptance criteria. Data & ML Validation
- Perform model validation testing and verify AI/ML output accuracy against business requirements.
- Validate raw data extracts, schemas, data lake inputs, and data quality thresholds.
- Conduct checks for completeness, duplicates, null handling, outliers, and coverage.
- Establish versioned test datasets and golden baselines for regression testing.
- Test model optimization outputs and implement quality guardrails. Automation & Engineering
- Implement automation using Python frameworks such as pytest, pandas, and NumPy.
- Develop and execute automated validation workflows for APIs, data pipelines, and ML-integrated applications.
- Create synthetic test data generators and golden fixtures for edge-case validation.
- Integrate testing workflows into CI/CD pipelines to enable continuous quality validation. Collaboration & Delivery
- Collaborate closely with Data Scientists, Engineers, and Product Teams to ensure quality delivery.
- Participate in Agile ceremonies and contribute to continuous improvement initiatives.
- Ensure high-quality releases through proactive defect identification and resolution tracking. Required Qualifications
- Bachelor's degree in Computer Science or related technical field.
- Strong coding experience in Java and/or Python.
- Solid understanding of software testing principles, automation strategies, and quality engineering practices.
- Strong analytical thinking and problem-solving skills.
Essential Experience
- Proven experience in Quality Engineering with exposure to AI/ML-based applications and analytics platforms.
- Strong understanding of manual and automated testing approaches for APIs, data pipelines, and distributed systems.
- Knowledge of ML concepts and algorithms such as regression, classification, clustering, and neural networks.
- Experience with model evaluation techniques, metrics, and validation strategies.
- Hands-on experience with SQL databases such as PostgreSQL.
- Experience working with CI/CD pipelines and automated testing workflows.
Preferred Skills
- Experience testing large-scale analytics or data-driven applications.
- Familiarity with cloud-based data platforms and distributed systems.
- Exposure to performance testing and scalability validation.
- Understanding of data governance and quality frameworks.
Core Competencies
- Quality-first mindset
- Analytical & problem-solving ability
- Automation & engineering excellence
- Attention to detail
- Collaboration & stakeholder communication
- Ownership and accountability Success Indicators
- High-quality and reliable ML/data platform releases
- Reduced production defects and data inconsistencies
- Effective automated regression coverage
- Improved confidence in AI/ML model outputs
- Strong collaboration across engineering and data teams
