Fastino.ai is looking for an ML Engineer to join its mission to develop specialized, efficient AI. You will own the full lifecycle of state-of-the-art small language models, from prototyping and data analysis to deployment and continuous improvement.

What You'll Do

Design, build, and deploy the critical small language models foundational to Fastino’s product.
Own the full lifecycle of state-of-the-art models, from prototyping to deployment, monitoring, and continuous improvement.
Drive the data strategy to improve model performance by analyzing distribution gaps, contributing to synthetic data pipelines, and creating automated annotation systems.
Experiment with novel language model architectures, helping drive and execute Fastino's research roadmap.
Implement reinforcement learning techniques including Direct Preference Optimization and Generalized Reward Preference Optimization to align model outputs with human preferences.
Build robust and real-world motivated evaluations.
Partner with the Fastino engineering team to ship model updates directly to customers.
Establish best practices for code health and documentation to facilitate collaboration and reliable development.

What We're Looking For

Advanced degree (Bachelors or Masters) in Computer Science, Artificial Intelligence, Machine Learning, or a related technical discipline with concentrated study in deep learning or 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.