AI / ML QA Engineer

Summary

Tests and validates AI/ML models (NLP, LLMs, classification) for accuracy, bias, and safety, designing test cases, automating workflows, and collaborating with data science teams.

Contract Duration: May 4, 2026 to November 4, 2026

Overview

We are seeking an experienced AI / ML QA Engineer to support testing and validation of advanced machine learning and generative AI systems. This role focuses on ensuring model quality, reliability, and responsible AI practices across a range of applications including NLP, classification, recommendation systems, and large language models.

Key Responsibilities

Functional and Model Testing

  • Design and execute test cases for AI and ML models including NLP, classification, recommendation, and generative AI systems
  • Validate outputs for accuracy, consistency, and expected behavior across diverse datasets and inputs
  • Perform regression testing following model updates, retraining cycles, or data changes

Prompt and LLM Testing

  • Develop and maintain prompt test libraries for LLM based features
  • Evaluate responses for relevance, tone, factual accuracy, and alignment with business rules
  • Identify hallucinations, response drift, and edge case failures

AI Safety and Red Teaming

  • Conduct adversarial testing to uncover vulnerabilities such as prompt injection and jailbreak scenarios
  • Assess outputs for bias, fairness, and compliance with responsible AI standards
  • Document risks and collaborate with model teams on remediation strategies

Test Automation and Tooling

  • Build and maintain automated test suites using Python based frameworks
  • Track and report quality metrics, model performance benchmarks, and defect trends

Collaboration and Documentation

  • Work closely with data scientists, ML engineers, and product teams
  • Develop clear test plans, defect reports, and evaluation summaries
  • Contribute to QA standards and best practices for AI systems

Required Skills

  • Hands on experience testing AI and ML models including NLP, classification, and generative AI
  • Strong experience with LLM testing including prompt engineering and evaluation of hallucinations, bias, and response quality
  • Proficiency in Python and test automation frameworks
  • Experience working with CI CD pipelines
  • Solid understanding of regression testing

Nice to Have

  • Experience in banking or financial services
  • Exposure to AI safety and red teaming techniques such as prompt injection and jailbreak testing
  • Knowledge of responsible AI and model governance principles
  • Familiarity with LLM evaluation tools and frameworks
  • Experience testing recommendation or ranking systems
  • Exposure to ML pipelines and MLOps workflows
  • Understanding of bias and fairness metrics

Note: We use AI tools to: obtain basic information, detect plagiarism, false employment history or references, categorize your skills, and do an initial match with job posting.

See also

QA jobs by country — openings, pay and top skills →

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