What You Will Be Doing in the Company
As a Member of Technical Staff, you will play a crucial role in scaling up ML models across GPUs and facilitating model inference via APIs. Joining an interdisciplinary team of machine learners, protein engineers, and biologists, you will collectively work towards revolutionizing the control of biology and the treatment of diseases. Your primary focus will involve applying, refining, and evaluating proprietary generative models to design new functional proteins for wet lab assays. You will be responsible for enabling and optimizing large-scale model training, building ML infrastructure for heterogeneous compute infrastructure, and assisting in optimizing model training. Additionally, you will work on enabling and optimizing model inference, exposing models via APIs, and packaging models for reuse. You will also be involved in productionizing model validation, building automated evaluation pipelines, and developing tools and infrastructure to support projects.
Qualities/Skills That the Company Hiring is Looking For
Proficiency in enabling large-scale model training, including experience in running training and inference on cloud hardware and distributing data across accelerators.
Strong background as an ML engineer with a track record of notable contributions to machine learning projects.
Extensive experience as a software engineer, including architecting and engineering software projects used in production.
Demonstrated ownership of successful commercial and/or academic research projects.
Mission-driven mindset with a passion for making a positive impact and a curiosity for problem-solving.
Ability to thrive in a dynamic, fast-paced environment and achieve goals efficiently.
Preferred: Academic background in natural sciences or experience in scaling a young biotech startup.
Desirable Things the Company Hiring is Looking For
Stay updated on the latest ML engineering developments and gain a strong understanding of protein and cell biology.
Participate in knowledge sharing activities and present at internal reading groups.
Attend and present at relevant conferences to enhance professional development.