Machine Learning Engineer (Remote) at Output Biosciences

Candidates should possess a Bachelor's degree in Computer Science, Machine Learning, or a related technical field and have over 3 years of experience in developing and implementing deep generative learning models. Proficiency in Python and at least one major deep learning framework (PyTorch, TensorFlow, or JAX) is required, along with experience in pre-training models and distributed computing environments. Expertise in deep learning and generative architectures like transformers, diffusion models, and autoencoders, as well as experience with terra-scale datasets and scaling models to billions of parameters, are essential. Strong understanding of machine learning fundamentals, including model architectures, optimization techniques, and evaluation metrics, is also necessary. Experience in designing and implementing efficient data pipelines, developing robust evaluation frameworks, ensuring data integrity, and collaborative software development practices are required. Bonus points include experience applying ML to biology or chemistry, contributions to open-source ML projects or published research, experience optimizing ML models for HPC, and familiarity with ML-Ops practices.