AI Intern at SWBC in San Antonio, TX

Summary: SWBC is seeking talented students to join their College Intern Program in San Antonio, Texas. The AI Intern will support the design, development, and operationalization of Generative AI and machine learning solutions, focusing on building AI-powered applications and contributing to MLOps workflows. Responsibilities: - Build AI-enabled applications and prototypes leveraging generative AI and ML capabilities (e.g., retrieval-augmented generation, summarization, classification) - Assist with MLOps pipelines: data/model versioning, training workflows, evaluation, packaging, and deployment processes - Support deployment and operations of models/services on AWS, including environment setup, basic CI/CD integration, and operational readiness tasks - Develop and maintain Python components such as APIs, inference services, evaluation scripts, and tooling - Participate in model testing and evaluation, including prompt experiments, performance benchmarking, and quality monitoring - Help document designs, experiments, and results; contribute to team standards and best practices - Collaborate with engineers and product stakeholders to translate requirements into deliverable AI features Required Qualifications: - Currently pursuing a degree in Computer Science, Engineering, Data Science, or a related field (undergraduate or graduate welcome) - Expected graduation date of December 2026 or later - Some hands-on experience with: Python (e.g., scripting, notebooks, basic software practices), ML/GenAI fundamentals (e.g., embeddings, transformers concepts, evaluation basics) - Familiarity with at least one of the following: AWS (e.g., S3, IAM, Lambda, EC2, CloudWatch, ECR, SageMaker, Jupyter notebooks), Basic API development (Flask/FastAPI), Git and collaborative development workflows - Strong communication skills and ability to work effectively in a corporate, cross-functional environment - Exposure to MLOps tools and practices (CI/CD, model registries, experiment tracking, monitoring) - Experience with LLM application patterns, such as: Retrieval-Augmented Generation (RAG), Prompt engineering, prompt evaluation, guardrails - Familiarity with containerization (Docker) and orchestration concepts - Understanding of software engineering fundamentals (unit tests, code reviews, documentation) - Deliver working prototypes or production-ready components that demonstrate measurable improvements (e.g., faster iteration, higher quality responses, improved reliability) - Contribute to repeatable, documented workflows for building and deploying AI solutions - Collaborate effectively with the team and communicate progress clearly Required Skills: Python, AWS, MLOps Important Skills: Machine Learning, API Development Nice-to-Have Skills: Communication Skills, Collaboration, Documentation Benefits: Competitive overall compensation package, Work/Life balance, Employee engagement activities and recognition awards, Years of Service awards, Career enhancement and growth opportunities, Leadership Academy and Mentor Program, Continuing education and career certifications, Variety of healthcare coverage options, Traditional and Roth 401(k) retirement plans, Lucrative Wellness Program