Epoch –a research institute that investigates trends in ML and the economic consequences of AI– is hiring a specialist in computing hardware to lead investigations into HPC computing for AI workloads. The role is full time, remote, and we can hire in many countries. Compensation is between $150,000 and $180,000 USD, not restricted to this currency. If you have questions or would like to share any leads, please write to us at firstname.lastname@example.org.
Epoch is hiring a specialist in computing hardware to lead investigations into HPC computing for AI workloads. As a ML Distributed Systems Senior Researcher at Epoch, this person will collaborate with our team on novel research related to the cost of compute, trends in compute usage and performance, and parallelism techniques and utilization. This work will be crucial for improving our understanding of the future of AI and its impacts on society.
Your day-to-day activities will be researching the latest developments in the field, discussing their implications with our team and international experts, and writing reports that inform our research and policy-making all over the world. Over the course of a year, we anticipate you will have produced 3-4 leading reports on the future of training and inference of frontier ML models.
Some examples of reports and papers you might lead as part of the role include:
The successful candidate will report directly to Epoch's director Jaime Sevilla, and work closely with associate director Tamay Besiroglu on models of the future of AI.
Epoch is a research institute that investigates trends in machine learning and the economic consequences of AI. Our work informs research and policy-making at the UK Department of Science, Innovation and Technology, Anthropic, the Centre for the Governance of AI, the Centre for Data Ethics and Innovation, Open Philanthropy, the Center for Security and Emerging Technology, and elsewhere. Epoch’s research has been cited in media publications such as the MIT Technology Review and The Economist, and underpins Our World In Data’s AI visualizations.
You can learn more about our work in this summary dashboard or our blog.