About Digy4 Digy4 is a Canadian enterprise SaaS company modernizing Quality Engineering, AI-driven test generation, enterprise reporting, RCA, performance engineering, and risk-first engineering for Fortune 500/2000 organizations. Job ID - DigyPE0052 Role Overview We are seeking a hands-on Development Lead with strong experience in React, Node.js, NoSQL, AWS services, and AI/GenAI...
About the projects: we are building LLM evaluation and training datasets to train LLM to work on realistic software engineering problems. One of our approaches, in this project, is to build verifiable SWE tasks based on public repository histories in a synthetic approach with human-in-the-loop; while expanding the dataset coverage to different types of tasks in terms of programming language,...
Our Client is on a mission to build the IPO process support of the future, and we're looking for passionate collaborators, innovators, advisors, and leaders who can get us there. As a QA Engineer, you will assist Client's digital technology team in coding, testing, debugging and maintaining the architecture of client solutions to support our brand websites. RESPONSIBILITIES • You will be...
About the Job We are seeking a highly skilled QA Engineer with expertise in Selenium/Cypress to join our dynamic team. Your role will involve collaborating with cross-functional teams, writing efficient test scripts, performing automation and manual testing, executing automated tests, and identifying and resolving any issues that arise. The ideal candidate will have a strong background in test...
About Digy4 Digy4 is a Canadian enterprise SaaS company modernizing Quality Engineering, AI-driven test generation, enterprise reporting, RCA, performance engineering, and risk-first engineering for Fortune 500/2000 organizations. Job ID - DigyPE0052 Role Overview We are seeking a hands-on Development Lead with strong experience in React, Node.js, NoSQL, AWS services, and AI/GenAI...
About the projects: we are building LLM evaluation and training datasets to train LLM to work on realistic software engineering problems. One of our approaches, in this project, is to build verifiable SWE tasks based on public repository histories in a synthetic approach with human-in-the-loop; while expanding the dataset coverage to different types of tasks in terms of programming language,...
About Digy4 Digy4 is a Canadian enterprise SaaS company modernizing Quality Engineering, AI-driven test generation, enterprise reporting, RCA, performance engineering, and risk-first engineering for Fortune 500/2000 organizations. Job ID - DigyPE0052 Role Overview We are seeking a hands-on Development Lead with strong experience in React, Node.js, NoSQL, AWS services, and AI/GenAI...
About the projects: we are building LLM evaluation and training datasets to train LLM to work on realistic software engineering problems. One of our approaches, in this project, is to build verifiable SWE tasks based on public repository histories in a synthetic approach with human-in-the-loop; while expanding the dataset coverage to different types of tasks in terms of programming language,...
About Digy4 Digy4 is a Canadian enterprise SaaS company modernizing Quality Engineering, AI-driven test generation, enterprise reporting, RCA, performance engineering, and risk-first engineering for Fortune 500/2000 organizations. Job ID - DigyPE0052 Role Overview We are seeking a hands-on Development Lead with strong experience in React, Node.js, NoSQL, AWS services, and AI/GenAI...
About the projects: we are building LLM evaluation and training datasets to train LLM to work on realistic software engineering problems. One of our approaches, in this project, is to build verifiable SWE tasks based on public repository histories in a synthetic approach with human-in-the-loop; while expanding the dataset coverage to different types of tasks in terms of programming language,...
About the projects: we are building LLM evaluation and training datasets to train LLM to work on realistic software engineering problems. One of our approaches, in this project, is to build verifiable SWE tasks based on public repository histories in a synthetic approach with human-in-the-loop; while expanding the dataset coverage to different types of tasks in terms of programming language,...
About the projects: we are building LLM evaluation and training datasets to train LLM to work on realistic software engineering problems. One of our approaches, in this project, is to build verifiable SWE tasks based on public repository histories in a synthetic approach with human-in-the-loop; while expanding the dataset coverage to different types of tasks in terms of programming language,...
About the projects: we are building LLM evaluation and training datasets to train LLM to work on realistic software engineering problems. One of our approaches, in this project, is to build verifiable SWE tasks based on public repository histories in a synthetic approach with human-in-the-loop; while expanding the dataset coverage to different types of tasks in terms of programming language,...
About the projects: we are building LLM evaluation and training datasets to train LLM to work on realistic software engineering problems. One of our approaches, in this project, is to build verifiable SWE tasks based on public repository histories in a synthetic approach with human-in-the-loop; while expanding the dataset coverage to different types of tasks in terms of programming language,...
About the projects: we are building LLM evaluation and training datasets to train LLM to work on realistic software engineering problems. One of our approaches, in this project, is to build verifiable SWE tasks based on public repository histories in a synthetic approach with human-in-the-loop; while expanding the dataset coverage to different types of tasks in terms of programming language,...
About the projects: we are building LLM evaluation and training datasets to train LLM to work on realistic software engineering problems. One of our approaches, in this project, is to build verifiable SWE tasks based on public repository histories in a synthetic approach with human-in-the-loop; while expanding the dataset coverage to different types of tasks in terms of programming language,...
About the projects: we are building LLM evaluation and training datasets to train LLM to work on realistic software engineering problems. One of our approaches, in this project, is to build verifiable SWE tasks based on public repository histories in a synthetic approach with human-in-the-loop; while expanding the dataset coverage to different types of tasks in terms of programming language,...
About the projects: we are building LLM evaluation and training datasets to train LLM to work on realistic software engineering problems. One of our approaches, in this project, is to build verifiable SWE tasks based on public repository histories in a synthetic approach with human-in-the-loop; while expanding the dataset coverage to different types of tasks in terms of programming language,...
About the projects: we are building LLM evaluation and training datasets to train LLM to work on realistic software engineering problems. One of our approaches, in this project, is to build verifiable SWE tasks based on public repository histories in a synthetic approach with human-in-the-loop; while expanding the dataset coverage to different types of tasks in terms of programming language,...
About the projects: we are building LLM evaluation and training datasets to train LLM to work on realistic software engineering problems. One of our approaches, in this project, is to build verifiable SWE tasks based on public repository histories in a synthetic approach with human-in-the-loop; while expanding the dataset coverage to different types of tasks in terms of programming language,...