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ResearchRemote / EUInternshipInternship
Research Engineer Intern
You will work alongside our research and engineering team on questions where AI and operational data meet clinical reality. This internship is for someone who wants to learn how to design experiments, evaluate models, and turn results into decisions a product team can actually use — not a thesis project, not a demo.
What you'll do
- Help define small, well-scoped research questions with a clear product purpose.
- Build evaluation harnesses, datasets, and prototypes under mentorship.
- Run experiments, log results carefully, and surface limitations honestly.
- Read related work and translate it into options the team can compare.
- Document hypotheses, methods, and findings so the next person can build on them.
What we look for
- Strong foundations in statistics, machine learning, NLP, HCI, or a related quantitative field.
- Comfort with Python and at least one analysis or ML stack (pandas, scikit-learn, PyTorch, or similar).
- Ability to read a paper, summarize it, and explain what is and is not useful.
- Care for reproducibility: seeds, versions, dataset provenance, eval scripts checked in.
- Clear written communication and willingness to ask for feedback early.
Plus if
- Prior coursework, publications, or open-source projects in LLM evaluation, RAG, ASR, or medical AI.
- Experience with prompt engineering, agent frameworks, or eval libraries (lm-eval-harness, ragas, etc.).
- Interest in healthcare data, clinical operations, or compliance-sensitive products.
What we offer
- Structured mentorship from senior research and engineering staff.
- Real research questions with direct product implications, not synthetic exercises.
- Access to evaluation infrastructure, internal datasets, and review feedback.
- A path to continue with the team — MTS Research Engineer or Software Engineer — for strong performers.