Overview Are you someone who is passionate, motivated, and driven to make a difference? If so, MSA Safety is the perfect fit for your career. At

MSA, SAFETY

is who we are AND it is what we do. We are a purpose-driven company committed to deploying innovation and technology to deliver on our Mission to help protect people and assets all around the world. We continue to be relentless in our pursuit of solving our customers greatest problems so they can go home safe each and every day. Are you in? Read on for more details about this particular role. Responsibilities We are seeking a highly motivated Co-op Intern to help advance our use of Artificial Intelligence (AI) within software testing and quality engineering. This role will focus on applying modern AI techniques to improve test selection, triage, defect analysis, workflow automation, and engineering productivity. The successful candidate will work closely with software engineering teams to design and prototype agentic workflows, develop AI-powered tools and skills, and evaluate emerging technologies that can improve the effectiveness and efficiency of our testing processes. Responsibilities Research, evaluate, and prototype AI technologies applicable to software testing and quality engineering. Design and implement agentic workflows for areas such as test selection, test prioritization, defect triage, root-cause analysis, and test result summarization. Develop and maintain AI agents, skills, prompts, and supporting automation to improve engineering workflows. Collaborate with software developers, test engineers, and product teams to identify opportunities for AI-driven process improvements. Build proof-of-concepts and pilot solutions using modern AI frameworks, APIs, and tooling. Analyze testing data and engineering metrics to improve test coverage, execution efficiency, and defect detection. Document solutions, findings, and best practices for broader organizational adoption. Present project progress, technical findings, and recommendations to stakeholders. Stay current with advancements in AI, machine learning, large language models (LLMs), and software testing methodologies. Qualifications Qualifications Currently pursuing a Bachelor's or Master's degree in Computer Science, Software Engineering, Computer Engineering, Data Science, Artificial Intelligence, or a related technical discipline. Strong academic performance and demonstrated technical aptitude. Experience developing software in at least one modern programming language such as Python, JavaScript/TypeScript, C#, Java, or C++. Familiarity with software development lifecycle processes and version control systems such as Git. Demonstrated interest in AI, machine learning, automation, or software quality. Strong analytical, problem-solving, and communication skills. Ability to work independently while collaborating effectively within a team environment. Special Knowledge, Skills, and Abilities Required Knowledge of software testing concepts, including unit, integration, system, and automated testing. Understanding of basic AI and machine learning principles Experience writing scripts or applications in Python or a similar language. Ability to analyze technical problems and propose practical solutions. Strong verbal and written communication skills. Ability to learn new technologies quickly and adapt to evolving priorities. Strong organizational skills and attention to detail. Ability to document technical work and communicate findings to both technical and non-technical audiences. Special Knowledge, Skills, and Abilities Preferred Experience with large language models (LLMs) and AI-assisted development tools. Familiarity with agent frameworks, prompt engineering, retrieval-augmented generation (RAG), or multi-agent systems. Experience building applications using AI APIs or platforms. Knowledge of software quality metrics, test automation frameworks, or continuous integration/continuous delivery (CI/CD) pipelines. Experience with Python testing frameworks such as pytest. Familiarity with cloud platforms, containerization technologies, or DevOps practices. Experience analyzing structured and unstructured data sets. Contributions to open-source projects, academic research, hackathons, or personal AI-related projects. Interest in applying AI to improve engineering productivity, software quality, and development workflows. This position offers a unique opportunity to help shape the future of AI-enabled software testing while gaining hands-on experience with emerging technologies, modern engineering practices, and real-world product development. #LI-GM1

Qualifications:

Qualifications Currently pursuing a Bachelor's or Master's degree in Computer Science, Software Engineering, Computer Engineering, Data Science, Artificial Intelligence, or a related technical discipline. Strong academic performance and demonstrated technical aptitude. Experience developing software in at least one modern programming language such as Python, JavaScript/TypeScript, C#, Java, or C++. Familiarity with software development lifecycle processes and version control systems such as Git. Demonstrated interest in AI, machine learning, automation, or software quality. Strong analytical, problem-solving, and communication skills. Ability to work independently while collaborating effectively within a team environment. Special Knowledge, Skills, and Abilities Required Knowledge of software testing concepts, including unit, integration, system, and automated testing. Understanding of basic AI and machine learning principles Experience writing scripts or applications in Python or a similar language. Ability to analyze technical problems and propose practical solutions. Strong verbal and written communication skills. Ability to learn new technologies quickly and adapt to evolving priorities. Strong organizational skills and attention to detail. Ability to document technical work and communicate findings to both technical and non-technical audiences. Special Knowledge, Skills, and Abilities Preferred Experience with large language models (LLMs) and AI-assisted development tools. Familiarity with agent frameworks, prompt engineering, retrieval-augmented generation (RAG), or multi-agent systems. Experience building applications using AI APIs or platforms. Knowledge of software quality metrics, test automation frameworks, or continuous integration/continuous delivery (CI/CD) pipelines. Experience with Python testing frameworks such as pytest. Familiarity with cloud platforms, containerization technologies, or DevOps practices. Experience analyzing structured and unstructured data sets. Contributions to open-source projects, academic research, hackathons, or personal AI-related projects. Interest in applying AI to improve engineering productivity, software quality, and development workflows. This position offers a unique opportunity to help shape the future of AI-enabled software testing while gaining hands-on experience with emerging technologies, modern engineering practices, and real-world product development. #LI-GM1