Software Engineering Development - AI​/Data Science Intern Austin

At IBM Software, we transform client challenges into solutions. Building the world’s leading AI-powered, cloud-native products that shape the future of business and society. Our legacy of innovation creates endless opportunities for IBMers to learn, grow, and make an impact on a global scale. Working in Software means joining a team fueled by curiosity and collaboration. You’ll work with diverse technologies, partners, and industries to design, develop, and deliver solutions that power digital transformation.

With a culture that values innovation, growth, and continuous learning, IBM Software places you at the heart of IBM’s product and technology landscape. Here, you’ll have the tools and opportunities to advance your career while creating software that changes the world.

Your role and responsibilities

We're building an AI Agentic Platform that powers enterprise‑grade analytics and financial intelligence products used by Fortune 500 companies. Our data engineering team operates at the cutting edge of AI/ML infrastructure — combining large‑scale cloud data platforms, agentic AI frameworks, and applied machine learning to solve complex business problems. We're looking for an exceptional intern who brings both the mathematical rigor of a quantitative background and the engineering chops to build production‑quality systems.

This is a role for someone who doesn't just want to run models — they want to understand why they work, help architect the platforms that run them, and grow into a full‑time engineer on a team that takes their craft seriously.

Required education

High School Diploma/GED

Preferred education

Bachelor's Degree

Required technical and professional expertise

• Contribute to the design and development of AI agentic workflows using frameworks like watsonx Orchestrate, Lang Chain, and AWS Bedrock
• Build and optimize data pipelines supporting ML model training, inference, and monitoring in Snowflake and cloud‑native environments
• Apply statistical and mathematical concepts to evaluate model performance, data quality, and system behavior
• Collaborate with data scientists, staff and principal engineers, and ML practitioners in an agile, sprint‑based environment
• Participate in architecture discussions and contribute to technical documentation and design reviews
• Explore and prototype emerging AI tooling and help the team evaluate new capabilities against platform need
• Pursuing or recently completed a degree that combines at least two of the following:
  Computer Science, Applied Mathematics, Statistics, or Data Science
• A dual major, interdisciplinary program, or strong coursework blend across these domains is highly preferred — we want someone who can think in equations and write clean code
• Strong Python skills — comfortable writing production‑quality code, not just notebook scripts
• Solid foundation in SQL and experience working with large datasets
• Understanding of statistical modeling, probability, linear algebra, and optimization concepts
• Exposure to machine learning frameworks (scikit‑learn, PyTorch, Tensor Flow, or similar)
• Familiarity with cloud platforms — AWS experience preferred
• Prior internship, research, or project experience in AI, data science, or ML engineering is strongly preferred
• Demonstrated ability to take a problem from ambiguous to structured — whether through academic research, a Kaggle competition, an open‑source contribution, or prior internship work
• Experience working with real‑world, messy data (not just clean classroom datasets) is a plus

• Familiarity with Dev Ops Tools:
  Exposure to Dev Ops tools and practices is beneficial for this role, allowing for smoother collaboration and automation in the software development lifecycle.
• Knowledge of Front‑End Development:
  Basic understanding of front‑end development principles and exposure to front‑end development frameworks can be advantageous in designing and delivering comprehensive software solutions.
• Understanding of L3 Support Engineering:
  Interest in L3 support engineering and exposure to debugging techniques can be helpful in resolving complex customer‑reported issues.

IBM Software…