Artificial General Intelligence

Our R&D and production teams are a combination of more research and more engineering-oriented profiles, however, everyone deeply cares about the quality of the systems we build and has a strong underlying knowledge of software development. We believe that good engineering leads to faster development iterations, which allows us to compound our efforts., Evaluation is one of the most important pillars of building a frontier model and product - it informs the direction of research and development, powers our experimentation and ensures quality and alignment with our users.

To support this, we need a powerful pipeline and self-serve evaluation framework that helps poolsiders build, run and extract insight from evals easily.

In this role, you will design and implement this platform to build and run evaluations at scale., * Design a Python framework that makes it easy for poolsiders to implement both internal and public benchmarks in a centralized way

• Build and maintain the pipeline that runs distributed evaluations at scale
• Collaborate with modeling and product teams to identify opportunities to improve our experimentation and evaluation tooling

• Strong engineering background
• Experience leading software projects cross functionally
• Experience building highly reliable and well tested services
• Experience with distributed systems
• Data pipelines, distributed processing
• Message queues, event-driven architectures, e.g. Kafka, Google pub/sub.
• Clouds: managed services, storage. GCP, AWS, Azure.
• Monitoring and alerting: Grafana, Prometheus, Datadog
• Plus: Experience designing frameworks or tooling for developers
• A product mindset towards building developer facing software
• A knack for collaborating with researchers and ML engineers to identify opportunities
• Plus: Experience with ML ops and data visualization platforms

In this decade, the world will create Artificial General Intelligence. There will only be a small number of companies who will achieve this. Their ability to stack advantages and pull ahead will define the winners. These companies will move faster than anyone else. They will attract the world’s most capable talent. They will be on the forefront of applied research, engineering, infrastructure and deployment at scale. They will continue to scale their training to larger & more capable models. They will be given the right to raise large amounts of capital along their journey to enable this. They will create powerful economic engines. They will obsess over the success of their users and customers.