AI ML Testers

Code1; India; Remote; INR 600,000 - 1,100,000; Full time

Job summary

Code1 Tech is seeking an experienced Risk Models Testing Lead to drive testing, validation, and QA of AI/ML models used in banking. You will collaborate with Data Scientists, Model Risk Management, and Compliance to ensure accuracy, explainability, and production readiness.

Responsibilities include designing testing strategies, validating PD/EAD/IFRS9, and leading GenAI/LLM validation. A strong banking background and hands-on testing experience are essential.

Qualifications

• Experience in Banking Technology, Risk, or Digital Transformation.
• Strong understanding of model governance and regulatory expectations.
• Experience in QA/testing AI/ML models and risk models.

Responsibilities

• Design and execute comprehensive testing strategies for AI/ML models used in banking.
• Validate model performance across training, validation, and production datasets.
• Perform functional, non-functional, regression, and end-to-end testing of AI-driven banking solutions.
• Assess model outputs against business expectations and regulatory requirements.
• Lead testing and validation of models supporting Credit Risk, PD, EAD, IFRS9 ECL, and related areas.
• Validate GenAI/LLM outputs, prompts, and retrieval-augmented generation workflows.
• Ensure data quality, lineage, and feature validation for model inputs.
• Develop automated testing frameworks and regression suites; deliver dashboards.

Skills

Retail Banking

Credit Risk

Basel II / Basel III

IFRS 9

Regulatory Reporting

Lending Lifecycle

Education

Bachelor’s degree in CS, Engineering, Maths, Statistics or Finance

Master’s degree (advantage)

Tools

Postman

PyTest

Robot Framework

JMeter

Job description

At Code1 Tech, we drive innovations that shape the future of enterprise technology. Our expertise spans Data Engineering, AI/ML, Cloud Solutions, and Full-Stack Development. We empower businesses with cutting-edge technology solutions, enabling digital transformation at scale. Join us to build impactful products with a passionate team of engineers and innovators.

About The Role

We are seeking an experienced Risk Models Testing Lead to drive the testing, validation, and quality assurance of AI and Machine Learning models used across the banking ecosystem. The ideal candidate combines deep banking domain expertise with hands-on experience testing AI/ML models used for credit risk, fraud detection, AML, collections, customer segmentation, pricing, and regulatory reporting.

The role requires close collaboration with Data Scientists, Model Risk Management, Product Owners, Technology, Business, and Compliance teams to ensure AI solutions are accurate, explainable, compliant, and production-ready.

Experience:

8–12 years of experience in Banking, Risk Management, AI/ML Product Delivery, or Model Validation.

Key Responsibilities:

• Design and execute comprehensive testing strategies for AI and Machine Learning models.
• Validate model performance across training, validation, and production datasets.
• Perform functional, non-functional, regression, and end-to-end testing of AI-driven banking solutions.
• Validate model outputs against business expectations and regulatory requirements.
• Assess model accuracy, precision, recall, F1 score, ROC-AUC, and other relevant performance metrics.
• Test model robustness under edge cases, stress scenarios, and adverse conditions.
• Lead testing and validation of models supporting:
• Credit Risk
• Probability of Default (PD)
• Exposure at Default (EAD)
• IFRS 9 Expected Credit Loss (ECL)
• Early Warning Systems
• AML Transaction Monitoring
• Collections Prioritization
• Credit Decisioning
• Pricing and Limit Management

GenAI & LLM Testing

• Validate Large Language Model (LLM) outputs for banking use cases.
• Test prompt engineering strategies and dynamic prompting frameworks.
• Evaluate hallucinations, bias, consistency, explainability, and confidence scoring.
• Perform retrieval validation for Retrieval-Augmented Generation (RAG) applications.
• Test AI copilots supporting credit underwriting, policy interpretation, and customer servicing.
• Ensure compliance with model governance frameworks and validation standards.
• Validate model documentation, assumptions, limitations, and approval criteria.
• Ensure adherence to regulatory expectations from central banks and internal governance teams.

Data Validation

• Validate data quality, completeness, lineage, and feature engineering.
• Verify data transformations and feature calculations.

Automation & Quality Engineering

• Develop automated testing frameworks for AI models.
• Maintain reusable test cases and regression suites.
• Produce detailed defect reports and testing dashboards.

Stakeholder Management

• Work with Risk, Business, Data Science, Compliance, Audit, Technology, and Product teams.
• Present testing findings and model readiness assessments to governance forums.
• Support User Acceptance Testing (UAT) and production readiness reviews.

Required Skills:

Banking Domain

• Retail Banking
• Credit Risk
• Basel II / Basel III
• IFRS 9
• Regulatory Reporting
• Lending Lifecycle

AI/ML

• Machine Learning lifecycle
• Explainable AI (XAI)
• Responsible AI
• Prompt Engineering
• GenAI Testing
• LLM-Evaluation
• RAG Validation
• Confidence Score Validation
• Bias & Fairness Testing

Testing Tools

• Postman
• PyTest
• Robot Framework
• JMeter
• API Testing
• Data Validation Tools

Technical Skills:

• SQL
• Python
• Jupyter Notebook
• Git
• REST APIs
• Snowflake
• Databricks (preferred)
• MLflow (preferred)

Experience Required:

• 10+ years in Banking Technology, Risk, or Digital Transformation.
• Minimum 5 years of experience testing or validating AI/ML models.
• Experience working with Data Scientists and Model Risk teams.
• Strong understanding of model governance and regulatory expectations.
• Experience in Agile and DevSecOps environments.

Preferred Qualifications:

• Bachelor’s degree in Computer Science, Engineering, Mathematics, Statistics, or Finance.
• Master’s degree is an advantage.
• Certifications in AI/ML, Data Science, Risk Management, or Banking.
• ISTQB Certification (preferred).
• Strong analytical and critical thinking skills.
• Excellent stakeholder management and communication.
• Ability to translate complex AI concepts into business outcomes.
• High attention to detail and risk awareness.
• Strong problem-solving and decision-making capabilities.
• Leadership experience managing cross-functional teams and complex banking transformation initiatives.