Principal Machine Learning Engineer

Health Futures is a Research and Incubation team working at the intersection of computer science, signal processing, machine learning, and biomedicine. We are a global and diverse team of engineers, scientists, and medical doctors who are working on next-generation Artificial Intelligence (AI) tools and methods for health and life sciences. We offer a unique and vibrant environment that features innovative academic research, enterprise software development, and real-world delivery, with close feedback loops and rapid iterations among all three, much like a lean startup. Our mission is to empower every person on the planet to live a healthier future. We are seeking a Principal Machine Learning Engineer to accelerate our training of generative models in close collaboration with Maching Learning (ML) researchers, software engineers, and domain experts. This is a hands-on technical role focused on advancing state-of-the-art model capabilities across a variety of scientific domains and modalities. You’ll spend your time working across the stack from curriculum design, to debugging training runs, through developing new evaluation methods and high-performance inferencing – with a goal of improving all phases of our training process. As part of Health Futures, you’ll have the opportunity to tackle everything from model training to data and evaluation pipelines. Your work will span the full spectrum of model development – training and optimizing models on the latest hardware, devising new ways to assess their capabilities, and evolving data and training workflows to maximize model utility. Beyond model training, you’ll participate in explorations of how these models can and should be used in the real world – and the systems required to successfully operate them.