Research Scientist, Together AI

• Can autonomously design, implement, and validate your research ideas
• Skilled at writing high-quality and efficient code in Python and PyTorch
• Have first-author publications at leading conferences on ML or NLP (ICLR, ICML, NeurIPS, ACL, EMNLP)
• Are a strong communicator, ready to both discuss your research plans with other scientists and explain them to broader audience
• Follow the latest advances in relevant subfields of AI
• Are passionate about seeing your research create real-world impact through Together AI's services and willing to work hands-on with production systems to achieve it

Desirable

• As a Research Scientist in Post-Training, you will advance the methods for making foundation models more useful and reliable
• You will analyze the limitations of current approaches to post-training across domains such as data curation, reinforcement learning, and model evaluation
• Based on this analysis, you will design new techniques for model adaptation, as well as benchmarks for measuring the progress in the field
• After evaluating your ideas through experimentation, you will present your findings to the global scientific community at leading ML/NLP conferences and collaborate with your teammates to integrate those improvements into Together’s platform
• Define and drive the research agenda around efficiency and performance of foundation model training
• Study recent results from the broader AI research community, analyzing their relevance to the team’s research directions and ongoing projects
• Conduct experiments to empirically validate your hypotheses and compare the outcomes with relevant related work
• Share your findings both internally and externally (e.g., at top-tier conferences on ML and NLP)
• Partner with Machine Learning Engineers to integrate advanced methods into Together’s Model Shaping platform