AI Engineering Intern

Your Journey at Crowe Starts Here: At Crowe, you can build a meaningful and rewarding career. With real flexibility to balance work with life moments, you’re trusted to deliver results and make an impact. We embrace you for who you are, care for your well-being, and nurture your career. Everyone has equitable access to opportunities for career growth and leadership. Over our 80-year history, delivering excellent service through innovation has been a core part of our DNA across our audit, tax, and consulting groups. That’s why we continuously invest in innovative ideas, such as AI-enabled insights and technology-powered solutions, to enhance our services. Join us at Crowe and embark on a career where you can help shape the future of our industry.

AI Engineering Intern Role Overview The AI Engineering Intern (Intern) supports the design, development, testing, and deployment of artificial intelligence solutions across the organization. This hands-on role provides exposure to core AI engineering practices—including model development, data preparation, and prototype creation—while contributing to supervised project tasks. Working closely with senior engineers, the intern builds foundational skills in coding standards, version control, evaluation techniques, and cloud-native development workflows. The intern collaborates with cross-functional teams, applies academic concepts to enterprise-scale systems, and gains the experience needed to grow into an entry-level engineering role.   This role emphasizes learning and skill development while delivering on assigned components, working under close supervision with frequent check-ins and code reviews, and building foundational technical skills and understanding of engineering practices. Successful interns demonstrate curiosity, initiative, and responsiveness to feedback. In this role, you will: Support the development of AI models and prototypes through data preparation, scripting, and experimentation Assist in implementing components of AI pipelines, including preprocessing, model training, and testing workflows Participate in code reviews and supervised engineering tasks to learn best practices Contribute to documentation of prototypes, experiments, and engineering processes Execute test cases and validation procedures to verify model performance and reliability Analyze datasets to extract insights and generate features under guidance Learn cloud-based tools, containerization, and orchestration concepts relevant to AI deployment Collaborate with team members to solve technical problems and complete scoped tasks Follow established coding, security, and compliance guidelines Explore emerging AI technologies and frameworks to build foundational understanding Qualifications Pursuing a degree in Computer Science, Engineering, Data Science, or a related field Working knowledge of foundational programming concepts and data structures, with exposure to Python Familiarity with core AI/ML concepts gained through coursework or independent projects Ability to communicate technical ideas clearly and collaborate effectively within a team Exposure to cloud platforms such as AWS, Azure, or GCP, along with containerization concepts including Docker and Kubernetes Introductory understanding of CI/CD practices and distributed computing fundamentals Curiosity-driven approach to learning, with responsiveness to feedback and coaching Some grounding in generative AI frameworks such as PyTorch, TensorFlow, or Hugging Face Beginning awareness of LLM concepts, including RAG workflows, vector databases, and fine-tuning techniques Preferred Qualifications Academic or project-based experience applying AI/ML concepts Awareness of low-code automation platforms such as Microsoft Power Platform (Power Apps, Power Automate) Familiarity with developer-focused AI tools such as Replit Agent or similar agentic coding platforms Minimum Knowledge Expectations All candidates for Crowe Studio