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 · RemoteDepartment: EngineeringReports to: Head of AIWork alongside: CTO, AI team, Engineering & ProductJob DescriptionLearnWise.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 doAI 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.RequirementsCore 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.