SDET Engineer

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

Bachelors 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