Science Intern

Key Responsibilities

• Research, design, and prototype innovative solutions using optimization, machine learning, large language models, agentic AI, and modern software engineering techniques.
• Develop software components, services, APIs, or analytical models that address real-world business challenges across Infor's ERP solutions.
• Evaluate emerging technologies, algorithms, frameworks, and foundation models to determine their applicability to enterprise software products.
• Design and implement scalable, maintainable, and well-tested code using modern development practices.
• Work with large datasets to develop, train, evaluate, and deploy data-driven solutions.
• Collaborate with scientists, engineers, product managers, and domain experts to deliver end-to-end technical solutions.
• Prototype integrations with existing product architectures and assess their impact on customer value, scalability, and operational efficiency.
• Maintain development artifacts, experiments, source code, and technical documentation in GitLab.

Skills, Knowledge & Expertise

• Final-year candidates in a Master's or Engineering program in Computer Science, Software Engineering, Artificial Intelligence, Data Science, Mathematics, Statistics, Physics, Operations Research, or a related quantitative discipline from an accredited university.
• Software development experience in Python and familiarity with software engineering fundamentals.
• Exposure to one or more of the following areas: machine learning, optimization, data science, artificial intelligence, distributed systems, or enterprise application development.
• Familiarity with scientific and data-analysis libraries commonly used in machine learning, optimization, and analytics.
• Basic understanding of SQL, data processing frameworks, or API-based application development.
• Familiarity with software development environments, source control using Git, and CI/CD practices.
• Strong analytical, problem-solving, and communication skills.

Benefits

• Experience or strong interest in machine learning, optimization, agentic AI, large language models, or modern software engineering.
• Familiarity with frameworks and tools such as PyTorch, Transformers, OR-Tools, Spring Boot, Node.js, Docker, or cloud platforms.
• Knowledge of data models, relational databases, and large-scale data processing.
• Exposure to modern AI architectures, foundation models, retrieval systems, or AI-agent frameworks.
• Familiarity with Agile development practices, Jira, and collaborative software development workflows.