– Create an automated service for iterating on network architectures. Most of the work is in defining and implementing the search space over network (which are, at the end of the day, just code that defines a graph of computations).
– Implement new tasks in Avalon and related environments. We are constantly extending our systems to add newer, more complex tasks on which to train more capable agents.
– Optimize existing agents and models to make them lower latency and higher throughput.
– Develop improved graphing, debugging, and error handling tools to investigate the myriad ways that neural networks and agents fail.
– Very comfortable writing Python.
– Familiar with PyTorch and training deep neural networks.
– Excited to work on open source code.
– Passionate about engineering best practices.
– Self-directed and independent.
– Excellent at getting things done
– Work directly on creating software with human-like intelligence.
– Actively co-create and participate in a positive, intentional team culture.
– Spend time learning, reading papers, and deeply understanding prior work.
– Salary: negotiation