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Job Description : - Role : Quality Assurance Engineer - Automation (3-4 yrs) - Location : Bengaluru - Type : Full-time Why this role? Join a fast-moving team that's pushing test automation into the AI era. You'll own end-to-end quality for web, mobile and API layers, combining Playwright (or similar) with next-gen, AI-driven test platforms to deliver smarter, faster releases. What you'll do : - Build & maintain automation with Playwright, Selenium, Cypress or equivalent - Super-charge coverage using AI-powered tools - Create, run and optimize manual, API (Postman/Rest Assured) and database (SQL) tests - Triage results, file defects in Jira, and drive them to closure What you bring : - 3-4 years' hands-on automation experience - Strong with Playwright (preferred) or Selenium/Cypress and one scripting language (JS/TS, Python or Java) - Familiarity with AI-based testing platforms - Solid API testing & SQL skills; sound grasp of STLC and defect management - Clear communicator with sharp analytical instincts - Nice to have : BDD (Cucumber/SpecFlow), performance testing (JMeter/LoadRunner), TestRail/Zephyr, ML model validation Qualifications : - Bachelor's in Computer Science, Engineering or related field What's in it for you ? - Hands-on exposure to cutting-edge AI test automation - Ownership and room to innovate in a collaborative, high-impact environment - Competitive pay, flexible policies and a fun tea

Bangalore

Draup - Quality Assurance Engineer - Automation Testing (3-6 yrs)

Responsibilities : - Model Development and Optimization : Design, build, and deploy NLP models, including transformer models (e.g., BERT, GPT, T5) and other SOTA architectures, as well as traditional machine learning algorithms (e.g., SVMs, Logistic Regression) for specific applications. - Data Processing and Feature Engineering : Develop robust pipelines for text preprocessing, feature extraction, and data augmentation for structured and unstructured data. - Model Fine-Tuning and Transfer Learning : Fine-tune large language models for specific applications, leveraging transfer learning techniques, domain adaptation, and a mix of deep learning and traditional ML models. - Performance Optimization : Optimize model performance for scalability and latency, applying techniques such as quantization, ONNX formats etc. - Research and Innovation : Stay updated with the latest research in NLP, Deep Learning, and Generative AI, applying innovative solutions and techniques (e.g., RAG applications, Prompt engineering, Self-supervised learning). - Stakeholder Communication : Collaborate with stakeholders to gather requirements, conduct due diligence, and communicate project updates effectively, ensuring alignment between technical solutions and business goals. - Evaluation and Testing : Establish metrics, benchmarks, and methodologies for model evaluation, including cross-validation, and error analysis, ensuring models meet accuracy, fairness, and reliability standards. - Deployment and Monitoring : Oversee the deployment of NLP models in production, ensuring seamless integration, model monitoring, and retraining processes.

Draup - Data Scientist - Deep/Machine Learning (1-3 yrs)

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Draup Careers, 2 Draup Jobs, July 2025  | hirist.tech

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