Cerebrone.ai
Website:
cerebrone.ai
Job details:
Job Title: Generative AI Engineer Intern
Location: Remote
Duration: 6 Months (extendable)
Compensation: Volunteer/Unpaid Opportunity
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We go beyond courses and tutorials. At Cerebrone.ai, interns and members build real GenAI systems—AI agents, RAG pipelines, memory layers, evaluation frameworks, and model-serving infrastructure—using production-grade tools and architectures.
Our community spans students, working professionals, startup founders, and enterprise engineers across the U.S. and globally. We emphasize:
• Learning by building
• Systems thinking over prompt hacking
• Open-source, research-backed GenAI engineering
• Agent-based architectures, not chatbots
Role Overview
We are seeking a Generative AI Engineer Intern who wants hands-on experience building agentic AI systems end-to-end.
You will work with the AgentVersity engineering team to design, build, and evaluate:
• AI agents
• LLM and SLM-based applications
• Memory-enabled systems
• RAG pipelines
• Model hosting and inference stacks
This role is ideal for candidates who want to deeply understand how GenAI systems work in practice, from architecture to deployment.
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What You’ll Learn & Work On
• Build applications using Large Language Models (LLMs) and Small Language Models (SLMs)
• Design and implement AI agents with tools, memory, and reasoning
• Work with LangGraph and/or Google Agent Development Kit (ADK)
• Build Retrieval-Augmented Generation (RAG) pipelines
• Understand agent memory (short-term, long-term, vector-based)
• Host and serve models using vLLM
• Compare closed vs open-source models
• Run LLM evaluations (quality, latency, cost, hallucination analysis)
• Learn tradeoffs in accuracy vs speed vs cost
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Responsibilities
• Assist in building GenAI-powered agents and applications
• Implement RAG pipelines using documents, embeddings, and retrievers
• Experiment with open-source LLMs and SLMs
• Support model inference and hosting using vLLM
• Design agent workflows using LangGraph or Google ADK
• Evaluate model outputs and improve system performance
• Document architectures, experiments, and learnings
• Collaborate with engineers on debugging and optimization
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Required Skills (Beginner to Intermediate)
• Strong interest in Generative AI and AI agents
• Programming experience in Python
• Basic understanding of:
• LLMs and transformers (conceptual level)
• Prompting and text generation
• Familiarity with Git and GitHub
• Curiosity, ownership, and willingness to learn fast
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Nice-to-Have Skills
• Experience with LangChain / LangGraph
• Exposure to Google ADK
• Knowledge of RAG architectures
• Familiarity with vector databases (FAISS, Chroma, Pinecone, etc.)
• Experience running models locally or on cloud GPUs
• Interest in evaluations, benchmarks, or model optimization
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Eligibility & Work Authorization
• US Citizens or Green Card holders preferred
• OPT and CPT candidates are welcome to apply
• Must be legally authorized to work in the U.S. (for paid roles)
• For unpaid roles, academic credit alignment is acceptable
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Who Should Apply
• Students or recent graduates in CS, AI, ML, or related fields
• Engineers transitioning into GenAI / AI agent roles
• Self-learners with GenAI projects or research interest
• Candidates who want deep engineering exposure, not surface-level demos
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What You’ll Gain
• Hands-on experience with real GenAI systems
• Exposure to agentic architectures used in industry
• Mentorship from engineers actively building AI products
• Portfolio-ready projects (agents, RAG systems, evaluations)
• Strong foundation for GenAI Engineer / AI Agent roles
- • Opportunity for full-time conversion or extended collaboration
Click on Apply to know more.