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AI Research Scientist – Multimodal Post-Training
Sword HealthAI Research Scientist focused on multimodal AI research and applications in healthcare at Sword Health. Building cutting-edge AI solutions to enhance patient understanding and care.
Tech Stack
Tools & technologiesPythonPyTorch
About the role
Key responsibilities & impact- Design and execute research on multimodal model training — with a primary focus on vision-language models and, increasingly, speech-language models — including fine-tuning, alignment, and post-training methods (SFT, RLHF) tailored for clinical domains;
- Develop and improve models that enable our AI agents to perceive and understand patients through video, language, and speech, building towards unified multimodal patient understanding;
- Contribute to the full model development cycle: multimodal dataset curation and annotation, architecture design, cross-modal training strategies, evaluation, and iteration;
- Collaborate across AI Engineering, Product, and Clinical teams to translate multimodal research breakthroughs into production systems that deliver patient care;
- Work towards long-term ambitious research goals — such as real-time multimodal patient state estimation, clinical memory, 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.
Requirements
What you’ll need- A PhD in Computer Science, Machine Learning, Natural Language Processing, Computer Vision, or a closely related AI field;
- Hands-on experience fine-tuning large language models or multimodal large models (e.g., vision-language models, speech-language models), including pre-training, SFT, RLHF, or related post-training techniques;
- Experience training or fine-tuning models that operate across multiple modalities (e.g., video + language, image + text, speech + text);
- 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.
Benefits
Comp & perks- Health, dental and vision insurance
- Meal allowance
- Equity shares
- Remote work allowance
- Flexible working hours
- Work from home
- Discretionary vacation
- Snacks and beverages
ATS Keywords
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Hard Skills & Tools
multimodal model trainingfine-tuningalignmentpost-training methodsSFTRLHFdataset curationarchitecture designcross-modal training strategiesmodel evaluation
Soft Skills
collaborationcommunicationresearchproblem-solvingexperiment designinterpretation of results
Certifications
PhD in Computer SciencePhD in Machine LearningPhD in Natural Language ProcessingPhD in Computer Vision