2 hours ago
Chicago, IL, USAIntern
Responsibilities
- Support AI model and prototype development through data preparation, scripting, and experimentation.
- Assist with preprocessing, model training, testing, and other AI pipeline components.
- Participate in code reviews and supervised engineering tasks.
- Document prototypes, experiments, and engineering processes.
- Execute test cases and validation procedures to evaluate model performance and reliability.
- Analyze datasets to extract insights and generate features under guidance.
- Learn cloud-based tools, containerization, orchestration, and AI deployment workflows.
- Collaborate on scoped technical problems while following coding, security, and compliance guidelines.
- Explore emerging AI technologies and frameworks.
Requirements
- Pursuing a degree in Computer Science, Engineering, Data Science, or a related field.
- Working knowledge of programming fundamentals and data structures, with exposure to Python.
- Familiarity with foundational AI/ML concepts through coursework or independent projects.
- Ability to communicate technical ideas clearly and collaborate effectively.
- Exposure to AWS, Azure, or GCP and containerization concepts including Docker and Kubernetes.
- Introductory understanding of CI/CD practices and distributed computing fundamentals.
- 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.
- Academic or project-based AI/ML experience is preferred.
- Awareness of Microsoft Power Platform, Power Apps, Power Automate, Replit Agent, or similar tools is preferred.
- Baseline knowledge of ML/AI literacy, prompt engineering, context management, model selection, fine-tuning, prompting, RAG, hallucination mitigation, guardrails, evaluations, security and PII awareness, responsible AI, LLM APIs, vector search, embeddings, agentic workflows, and enterprise AI use cases.
- Demonstrated intellectual curiosity, attention to detail, analytical thinking, tenacity, communication, and responsiveness to feedback.
Benefits
- Inclusive culture focused on career growth, diversity, well-being, and professional development.
- Consistent meetings with a Career Coach to support career goals and aspirations.
- Learning opportunities through supervised engineering work, code reviews, coaching, and feedback.
Tech Stack
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