Experiment with novel language model architectures, helping drive and execute Fastino's research roadmap
Optimize Fastino’s multimodal models to improve response quality, instruction adherence, and overall performance metrics
Architect data processing pipelines, implementing filtering, balancing, and captioning systems to ensure training data quality across diverse content categories
Implement reinforcement learning techniques including Direct Preference Optimization and Generalized Reward Preference Optimization to align model outputs with human preferences and quality standards
Build robust and real-world motivated evaluations
Partner with Fastino engineering team to ship model updates directly to customers
Establish best practices for code health and documentation on the team, to facilitate collaboration and reliable development

Advanced degree (Master's or PhD) in Computer Science, Artificial Intelligence, Machine Learning, or related technical discipline with concentrated study in deep learning and computer vision methodologies
Demonstrated ability to do independent research in Academic or Industry settings
Substantial industry experience in large-scale deep learning model training, with demonstrated expertise in at least one of Large Language Models, Vision-Language Models, Diffusion Models, or comparable generative AI architectures
Comprehensive technical proficiency and practical experience with leading deep learning frameworks, including advanced competency in one of PyTorch, JAX, TensorFlow, or equivalent platforms for model development and optimization

Research Scientist

Key skills