{"@context":"https://schema.org","@type":"JobPosting","title":"Large Language Model (LLM) Intern","description":"

\n 📝 Large Language Model (LLM) Intern (Unpaid)\n

\n ⚠️ Applications will only be accepted through the following site: 👉 www.owlera.site\n

\n \n

\n About Owlera\n

\n Owlera is an AI-powered career platform that helps students and fresh graduates gain practical experience through internship simulations inspired by real companies. Participants work on realistic business challenges, receive AI-powered feedback, use modern professional tools, and build portfolio-ready projects that demonstrate their abilities to future employers.\n

\n We're looking for curious, analytical, and ambitious students to join our Large Language Model (LLM) Internship and gain hands-on experience with the technology at the heart of the AI revolution — large language models, their internals, and how they're deployed in real products.\n

\n\n

\n About the Internship\n

\n As a Large Language Model (LLM) Intern, you'll work on realistic challenges centered on large language models — how they're trained and fine-tuned, how they reason, how they're evaluated, and how they're turned into production-ready features. You'll learn how AI engineers go from a raw pre-trained model to a reliable product — data curation, training and adaptation, evaluation, prompt design, and the engineering that keeps models fast, safe, and useful.\n

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\n Responsibilities\n

Explore the fundamentals of large language models — tokenization, attention, and transformer architectures.
Fine-tune and LoRA/PEFT-adapt open-weight models for specific tasks.
Build LLM evaluation pipelines (accuracy, robustness, hallucination, bias checks).
Curate and clean training and evaluation datasets.
Implement retrieval-augmented generation (RAG) over document collections.
Design structured prompts and prompt templates for classification, extraction, and reasoning.
Experiment with function calling and tool use in LLM workflows.
Work with embeddings, vector databases, and semantic search.
Benchmark different LLMs on the same task (quality, latency, cost tradeoffs).
Implement guardrails — output validation, content filtering, and refusal behavior.
Quantize and optimize models for faster, cheaper inference.
Analyze model failures and document fixes and lessons learned.
Build simple demos and interfaces (Streamlit, Gradio, or web frontends) around LLMs.
Track experiments and write clear documentation of results.
Collaborate with other interns on cross-functional AI projects.
Translate real-world problems into LLM-powered product formulations.

\n\n

\n Requirements\n

Current student or recent graduate in Computer Science, AI, Data Science, or a related field — or a strong self-taught coding portfolio.
Strong interest in large language models and how they work.
Basic programming skills (Python is a plus).
Comfortable with basic math — probability, statistics, and linear algebra at an introductory level.
Analytical and logical thinking with close attention to detail.
Self-motivated and able to work independently on technical challenges.
Comfortable experimenting, failing fast, and iterating.
Familiarity with AI tools such as ChatGPT, Claude, Gemini, or similar platforms is a plus.
Previous professional machine-learning experience is not required.

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\n What You'll Gain\n

Hands-on experience adapting and evaluating large language models, not just theory.
Practical experience with fine-tuning, RAG pipelines, and LLM evaluation.
Understanding of how LLM features are designed, shipped, and iterated.
Practical exposure to modern LLM APIs, open-weight models, and inference optimization.
Portfolio-ready LLM projects built on realistic use cases.
Personalized AI feedback on your work.
Professional certificate upon successful completion.
Mentorship and weekly learning sessions.
Opportunity to strengthen your portfolio, resume, and interview readiness.

\n\n

\n Internship Details\n

\n Role: Large Language Model (LLM) Intern
\n Location: Remote
\n Type: Internship (Unpaid)
\n Level: Entry Level
\n Duration: 6 Weeks
\n Commitment: Flexible (approximately 10–15 hours per week)
\n

\n\n

\n If you're fascinated by how large language models actually work and want to learn how real LLM-powered products are built, we'd love to hear from you.\n

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\n ⚠️ Apply through: 👉 www.owlera.site\n

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