About the job
About ai&
ai& is an innovative global AI technology firm committed to addressing the surging demand for artificial intelligence solutions. Our dual vision is to establish ourselves as a leading AI laboratory focused on localization while providing essential global infrastructure and computing resources. We are developing a cohesive, optimized platform that seamlessly integrates state-of-the-art data centers, diverse computing services, and advanced model capabilities. We believe that true AI scalability comes from managing the entire stack comprehensively.
At ai&, we empower small teams with the independence necessary to confront significant challenges. Our strategy involves breaking down complex problems into achievable tasks and collaboratively solving intricate issues. We are in search of highly driven, mission-oriented individuals who exhibit strong personal initiative. We value curiosity as a core component of talent and seek individuals eager to grow alongside our evolving technology and expanding business.
We are actively recruiting talent globally, with offices in Tokyo, San Francisco, Austin, and Toronto. We are excited to connect with exceptional candidates wherever they may be.
Role Overview
This position encompasses both research and engineering responsibilities. You will manage the complete post-training processes for ai&'s proprietary models and adapt models for enterprise clients needing domain-specific solutions. This includes conducting experiments, constructing necessary pipelines, and delivering actionable results.
You will collaborate directly with enterprise clients to transform their needs into effective post-training workflows, overseeing the delivery process, and ensuring that all applied insights are reintegrated into ai&'s foundational stack. Additionally, you will actively contribute to our reinforcement learning initiatives, designing training environments, incorporating cutting-edge research techniques, and developing the continual learning infrastructure that ensures our models consistently improve.
We seek an individual capable of viewing data, training, alignment, and evaluation as an interconnected system while being pragmatic enough to prioritize model quality and tangible outcomes above all.
