• Design and execute research on LLM fine-tuning, alignment, and post-training methods (SFT, RLHF) tailored for clinical and therapeutic domains;
• Develop and improve foundational AI models that power our AI agents, spanning language, vision, speech, and multimodal systems;
• Contribute to the full model development cycle: dataset curation and annotation, architecture design, training, evaluation, and iteration;
• Collaborate across AI Engineering, Product, and Clinical teams to translate research breakthroughs into production systems that deliver patient care;
• Work towards long-term ambitious research goals, such as clinical memory, long-horizon planning, and safety validation, while identifying and delivering immediate milestones;
• Advance the field by publishing in top-tier AI venues and clinical journals, contributing to Sword's growing body of peer-reviewed research.
• A PhD in Computer Science, Machine Learning, Natural Language Processing, or a closely related AI field;
• Hands-on experience fine-tuning large language models (pre-training, SFT, RLHF, or related post-training techniques);
• A strong publication track record in peer-reviewed AI conferences or journals;
• Proficiency in Python and deep experience with modern ML frameworks (e.g., PyTorch, JAX);
• Demonstrated ability to design rigorous experiments and interpret their results.