Top Tech Jobs & Startup Jobs

The UX Designer at Red Hat will work on AI/ML products, contributing to open-source projects, creating design artifacts, and collaborating with developers and users to enhance user experience. Responsibilities include evaluating software, delivering visual designs, and engaging with the community to integrate feedback into designs.

The Software Quality Engineer will develop and implement test strategies, craft automated tests, participate in quality practices, and explore potential biases in AI/ML models. The role involves collaborating with various stakeholders and contributing to open source AI projects.

As a Full Stack Software Engineer at Red Hat, you will design, develop, and optimize software tools focusing on AI/ML technologies, ensuring user experience primarily through command line interfaces. You will engage in automated testing, code reviews, and collaborate openly with upstream open source communities.

As a Software Engineer at Red Hat, you'll design and develop software tools for customizing machine learning models while adhering to coding standards and best practices. You'll engage with AI/ML communities, contribute to product features, and communicate effectively with stakeholders and team members.

As a Senior Software Quality Engineer at Red Hat, you will define and implement automated test strategies, execute tests, collaborate with the SW Quality team, analyze source code, develop test automation frameworks, and communicate progress to stakeholders. Your goal will be to ensure the quality of software contributions to key open source AI communities.

The Senior Software Engineer will develop open source IDE plugins for AI-based coding assistance, focusing on creating seamless user experiences in collaboration with design and product teams. Responsibilities include writing TypeScript code, engaging with open source communities, maintaining plugins on the VSCode Marketplace, and adhering to coding best practices and standards.

The role involves onboarding new technical associates in the AI Engineering organization, delivering enablement materials, guiding project planning and monitoring activities, collaborating on product requirements, and participating in status meetings. Strong technical leadership and communication skills are essential.