Machine Learning Engineer (Remote)

The Role Join our team and help build the world's first biological reasoning model. Work with us to build generative foundational models that decode biological systems across scales - from molecules to organisms - enabling us to predict, understand, and program living systems in ways never before possible. Output is currently in stealth, operated by a team of repeat founders and biotech veterans with multiple exits in AI x Bio, and backed by top-tier VCs including Y Combinator. As a Machine Learning Engineer, you'll work alongside our founders and team members to develop and implement cutting-edge AI systems capable of complex biological reasoning across multiple scales. - You will build foundational models for biology capable of reading and writing biology at scale - You will develop deep generative models for biological applications, exploring innovative architectures to capture the complexities of multi-scale biological systems - You will work on distributed training systems to scale our models to billions of parameters, optimizing for performance and efficiency across multi-GPU and multi-node setups while handling large-scale biological datasets - You will engineer efficient data pipelines to manage and process massive biological datasets, addressing challenges in data loading, splitting, and memory optimization - You will develop and implement robust evaluation frameworks for complex biological models, ensuring data integrity and preventing leakage across dataset splits Who We're Looking For - You have a Bachelor's in Computer Science, Machine Learning, or a related technical field - You have 3+ years of experience in developing and implementing deep generative learning models - You have experience pre-training models and are proficient in distributed computing environments - You are proficient in Python and have expertise in at least one major deep learning framework (PyTorch, TensorFlow, or JAX) - You have experience with deep learning and generative ar