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Sr Eng, Test

India, Bengaluru · Job Posted April 27, 2026
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Job Description

We are seeking an Senior Automation Engineer with 6+ years strong hands-on experience in AI/ML model validation and testing. This role focuses on ensuring the quality, reliability, accuracy, and robustness of AI/ML and LLM-based systems through systematic validation, data quality checks, and automated evaluation pipelines. The ideal candidate has solid experience working with supervised ML models, LLMs, and ML pipelines, strong Python-based validation scripting skills, and a deep understanding of data, model behavior, and evaluation metrics.

Job Responsibility

  • Design and execute validation strategies for AI/ML models, including supervised learning models and large language models (LLMs)
  • Perform functional, regression, and behavioral testing of ML models across versions
  • Validate model outputs for accuracy, consistency, bias, and edge cases
  • Evaluate LLM responses for correctness, relevance, hallucinations, and safety
  • Design and implement data quality validation checks for training, validation, and inference datasets
  • Detect and analyze data drift and concept drift across model iterations and production data
  • Validate input data assumptions, feature distributions, and schema consistency
  • Collaborate with data and ML engineers to identify and resolve data-related issues impacting model performance
  • Develop Python-based validation scripts and frameworks to automate model evaluation, data validation, and regression testing across model versions
  • Implement automated checks for model performance metrics (precision, recall, F1, accuracy, etc.)
  • Build reusable validation utilities that integrate with ML workflows and pipelines
  • Execute LLM evaluation workflows including prompt-response validation, golden dataset comparisons, and regression testing across prompt or model changes
  • Contribute to evaluation strategies for RAG or multi-step LLM pipelines
  • Support responsible AI initiatives by testing bias, robustness, and failure modes
  • Work closely with ML engineers, data scientists, platforms, and product teams
  • Actively participate in requirement discussions and model review sessions
  • Clearly document test results, risks, and quality insights for stakeholders
  • Contribute to continuous improvement of AI testing practices and standards

Requirements

  • 4+ years of hands-on experience in AI/ML model testing, validation, or quality engineering
  • Strong proficiency in Python for model validation and data analysis
  • Experience validating supervised ML models and/or LLM-based systems
  • Solid understanding of ML evaluation metrics and validation techniques
  • Experience with data quality checks, drift detection, and dataset validation
  • Familiarity with ML pipelines and model lifecycle (training, validation, inference)
  • Ability to analyze model behavior and explain quality risks clearly
  • Good communication and collaboration skills

What we offer

  • Support for Parents
  • Continuing Education/ Professional Development
  • Employee Health & Well-Being Benefits
  • Paid Time Off
  • 2 Days a Year to Volunteer

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