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AI Engineering Intern (LLM Ops & RAG)

AI Engineering Intern (LLM Ops & RAG)

LearnWise AImálaga, andalucía, Spain
Hace 20 días
Descripción del trabajo

LearnWise is a company where the best idea always wins — no matter what — and where innovation and hyper-growth are in our DNA.

We offer Engineering internships designed to build future technical leaders - hopefully at LearnWise!

Internship

  • EU
  • Remote

Department : Engineering

Reports to : Head of AI

Work alongside : CTO, AI team, Engineering & Product

Job Description

LearnWise.ai is a scale-up modernizing educational institutions with virtual assistants, instructor efficiency, and student engagement solutions for higher education. We’re seeking an inspired and rigorous Engineering Intern for a 6-month internship focused on AI systems, reliability, and product behavior.

You’ll join a VC-funded team with a track record of exponential growth. You’ll work closely with leadership and be expected to propose, test, and ship your own ideas.

What you’ll do

AI Systems & Reliability

  • Troubleshoot LLM behavior and agent actions across our Tutor Assistant, automatic feedback, and other AI features; identify root causes and ship fixes.
  • Use LangSmith, LogFire and other tools to trace requests end-to-end, correlate prompts, tools, and outputs, and explain why a behavior occurred.
  • Implement pragmatic guardrails, fallbacks, and caching; reduce failure modes and improve correctness under real usage.
  • Retrieval & Relevance

  • Optimize our retrieval pipelines : choose and tune embeddings, refine vector-database indexing / search strategies, and evaluate re-rankers for higher precision / recall.
  • Design and run experiments (e.g., recall@k, MRR, nDCG, groundedness checks) that translate directly into product wins.
  • LLM Ops & Tooling

  • Contribute to LLM Ops : prompt / tool versioning, dataset curation, regression test suites, latency / cost monitoring, and safe rollout strategies (shadow, A / B).
  • Build small utilities to surface failure taxonomies, detect drift, and turn traces into actionable fixes.
  • Grow into feature development that measurably improves product quality and student outcomes.
  • Collaboration & Strategy

  • Partner with the Head of AI, CTO, AI team, Engineering, and Product to shape technical direction.
  • Share learnings clearly; propose changes that improve model performance, reliability, and UX.
  • Requirements

    Core Requirements

  • Strong proficiency in Python.
  • Master’s (ongoing or completed) in AI / ML or a related field, or equivalent experience demonstrating comparable depth.
  • Solid understanding of modern AI models and AI-powered applications (prompting, tool-use / agents, RAG, context management, evaluation).
  • Hands-on experience with LLMs and / or tool-using agents : debugging prompts, tracing tool calls, analyzing failure modes.
  • Ability to design evaluation loops (golden sets, regression tests, online experiments) that make reliability measurable and improvable.
  • Ability to figure things out independently and chase issues until completion.
  • Nice to Have

  • Experience optimizing RAG components : embeddings selection / tuning, vector DB configuration, re-ranker selection / evaluation.
  • Familiarity with AI observability / monitoring practices and failure taxonomies.
  • Fluent in English; direct, candid communication style; hungry to learn and ship.
  • What’s in it for you?

  • Direct mentorship from senior leadership (CTO, Head of AI, Head of Product).
  • Work with a global team on cutting-edge AI applications.
  • Flexible working arrangements (results >
  • hours).

  • A “no 9-to-5 mentality” and genuine focus on work-life balance.
  • If you’re passionate about engineering with AI, eager to learn, and excited to work in a fast, practical startup environment, this is your chance to build AI that meaningfully improves student outcomes. We’d love to hear from you.

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