We’re hiring exceptional people to help us solve hard problems, design and build our product, shape our culture, and grow our company. We value diversity in opinions and background. We also value open communication, collaboration, and empathy.
We are conveniently located in South of Market, San Francisco, a quick 7-minute walk from the Powell Street MUNI/BART station.
As a Systems Engineer, you will tackle challenging problems at the cutting edge of deep learning research and development, and collaborate with leading machine learning engineers. You will have the opportunity (and responsibility!) to define major aspects of our product: you’ll be expected to take on a difficult problem without a clear solution, and to design, build, and iterate until we’ve reached an elegant solution that delights our customers. You will work on problems such as efficient cluster scheduling over heterogeneous GPUs, implementing cutting-edge algorithms for hyperparameter optimization, and designing systems for managing ETL pipelines and automated deployment of deep models.
As a Senior ML Engineer, you will have the opportunity (and responsibility!) to define major aspects of our product vision and guide the product roadmap. You’ll work closely with our technical customers to better understand their actual pain points when developing and deploying deep learning workflows; develop prototypes for new product functionality inspired by both customer feedback and cutting-edge deep learning research; and interact with our world-class systems engineers to translate these ML prototypes into production-quality product features.
As a Frontend Engineer, you will be responsible for designing and implementing our products' web interfaces, and more broadly, will play a key role in defining how our customers interact with our products. You will build software to help researchers launch new deep learning workloads, monitor cluster utilization via a dashboard interface, and plot metrics to understand the statistical behavior of their experiments. You will help design a collaborative development environment for machine learning teams that spans the ML lifecycle from data management and model development through deployment and monitoring.