Alignment Scientist/Engineer
Join the alignment research team to work on high-impact, under-resourced projects focused on AI alignment. This role requires strong ML research and Python skills to build, train, or evaluate deep learning models.
As a Research Engineer, you will conduct and enable cutting-edge research, translating it into the core product pipeline. You will develop and improve state-of-the-art data curation strategies, accelerating research and ensuring product innovation.
As a Research Engineer, you will play a crucial role in conducting and enabling cutting-edge research and translating it into our core product pipeline. You will work closely with other members of the technical staff to develop and improve state-of-the-art data curation strategies. Your technical skills will accelerate our research and ensure that our product remains at the forefront of innovation.
At DatologyAI, we are dedicated to rewarding talent with highly competitive salary and significant equity. The base salary for this position ranges from $180,000 to $300,000. The candidate's starting pay will be determined based on job-related skills, experience, qualifications, and interview performance.
We offer a comprehensive benefits package to support our employees' well-being and professional growth:
Join the alignment research team to work on high-impact, under-resourced projects focused on AI alignment. This role requires strong ML research and Python skills to build, train, or evaluate deep learning models.
Research Scientist investigates training data interventions to improve deep learning model quality and behavior. Sources ideas from literature, conducts customer-grounded research, and collaborates with engineers to deliver impact. Requires 3+ years deep learning research and PyTorch proficiency.
Develops state-of-the-art Visual Question Answering systems for medical records using advanced NLP and Computer Vision techniques. Requires expertise in these fields, strong software engineering skills, and ability to work with noisy data to achieve production-scale model performance.
Leads research on post-training data curation for foundation models, designing algorithms to generate/improve instruction and preference datasets, and unifying pre/post-training optimization. Requires 3+ years deep learning research, post-training experience with vision/language/multimodal models, and PyTorch proficiency.
Develops scalable voice interface features through prototyping, infrastructure building, and R&D. Requires PhD in ML or related field, top conference publications, Python/LLM fluency, and strong engineering skills.