(Seoul) Applied Research Scientist · AI Innovation - 전문연 가능

"Conquering cancer through AI" Lunit, a portmanteau of ‘Learning unit,’ is a medical AI software company devoted to providing AI-powered total cancer care. Our AI solutions help discover cancer and predict cancer treatment outcomes, achieving timely and individually-tailored cancer treatment.

🗨️ About the Team Who will I spend 8+ hours/day with? • You will join the AI Innovation team behind the Chain-of-Evidence (CoE) project, also known as 특화 파운데이션 모델 project. The team brings together AI research scientists and engineers across RAG & Product, Model & Evaluation, and Data & Knowledge, building real products while tackling meaningful applied research along the way. • Members have diverse backgrounds and interests — some are passionate about LLM training and evaluation, others about retrieval and knowledge systems, others about productization and clinical deployment — united by a shared commitment to improving patient care. • This team is a fast paced “full stack” team, where ideation to deployable PoC happens in rapid iteration cycles. The team gets to work on strategically important initiatives aligned to enabling new business opportunities for Lunit.

🗨️ About the Position What will make me proud to work here? • You will have a direct impact on bringing trustworthy, evidence-grounded AI into real clinical workflows — clinical intelligence and agentic applications — deployed and evaluated together with partner hospitals. • Your work will push forward the performance of Lunit's medical foundation models, RAG systems, and agentic pipelines that power Lunit’s next generation clinical intelligence. • We work with large-scale clinical knowledge sources (medical literature, clinical guidelines, insurance and EMR data) and the cloud/GPU compute to leverage them. • Current work spans LLM post-training (SFT/SDFT), retrieval-augmented generation, agentic reasoning, faithfulness and citation evaluation, and live clinical deployment — among others. • As an early-career scientist, you will grow fast — owning real features end-to-end, learning from a strong multi-disciplinary team, and meeting the actual medical professionals who will be using our systems.

🚩 Roles & Responsibilities • Build, implement, and help design components of ‘Clinical Intelligence’: medical foundation models, LLM- and retrieval-based AI systems that address real-world clinical problems. • Rapidly turn ideas into working prototypes and deployable PoCs, iterating quickly with the team. • Contribute to the core components of ‘Clinical Intelligence’ — medical RAG, agentic reasoning pipelines, context management, LLM post-training (SFT/SDFT/RL), and evaluation of faithfulness, citation quality, and hallucination. • Write high-quality, well-tested code in our internal research codebases, following solid engineering practices. • Collaborate with clinical partners (hospitals, medical doctors) and product teams to ship systems clinicians actually use.