MetricStream is seeking an AI Intern to develop GRC (Governance, Risk, and Compliance) use cases at the intersection of design, AI, and enterprise challenges, aiming to build and deploy AI-driven solutions and agents.
Requirements
- Strong programming skills in Python.
- Familiarity with LLMs, prompt engineering, or agentic workflows
- Understanding of LangChain, LangGraph, or similar frameworks (academic, project, or professional exposure).
- Knowledge of RAG patterns, embeddings, and similarity checks.
- Exposure to vector databases and AI/ML libraries (PyTorch, TensorFlow, Hugging Face).
- Curiosity and eagerness to learn about foundation model fine-tuning (LoRA, DSPy) and multi-agent systems.
- Experimenting with AI on the side
Responsibilities
- Solutioning problems using user-centric design techniques, leveraging modern architectures and AI.
- Build production-ready AI use cases leveraging LLMs, agents, and context engineering solutions.
- Design and implement memory and knowledge solutions, including RAG validation with custom scripts and embedding-based similarity checks.
- Develop AI-driven information discovery solutions like semantic search using vector databases (e.g., Pinecone, FAISS, Weaviate).
- Explore foundation models and fine-tuning techniques (LoRA, DSPy, adapter frameworks) while optimizing performance, cost, and security.
- Work with ML libraries (PyTorch, TensorFlow) and experiment with RNN/CNN architectures.
- Collaborate with mentors to solution AI/ML use cases in the GRC domain, working directly with stakeholders in client-facing engagements.
Other
- Currently enrolled in or recently graduated with a Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field. Alternatively, if you’ve been self-learning and experimenting independently and are confident in your skills, we’d love to hear from you.
- Strong problem-solving, analytical, and research abilities.
- Ability to thrive in a fast-paced, client-facing environment, working with business teams to align technical solutions with real-world needs.
- Document findings, prototype results, and contribute to knowledge-sharing initiatives in a fast-paced delivery environment.
- Enthusiastic and motivated
