About the job
Join Our Innovative Team
Adaptive ML is at the forefront of AI technology, crafting a state-of-the-art Reinforcement Learning Operations (RLOps) platform. Our mission is to empower enterprises to specialize and deploy large language models (LLMs) in production to achieve significant outcomes.
We are the backbone for tuning, evaluating, and serving specialized models at scale, revolutionizing task-specific LLM development. Our infrastructure supports production-ready workflows that handle millions of requests efficiently while optimizing for performance and cost across distributed systems.
Our cohesive team has previously contributed to the development of leading open-access large language models. Having secured a $20M seed funding from Index Ventures and ICONIQ in early 2024, we are already operational, serving clients such as Manulife, AT&T, and Deloitte in the travel and financial sectors, with more partnerships on the horizon.
The Product Staff at Adaptive ML is dedicated to translating our advanced technology into exceptional products that address the challenges faced by companies in their generative AI deployments. We are committed to creating a high-quality, user-friendly, and resilient experience for our clients.
Your Role
As a DevOps Engineer within our Product Staff, you will play a crucial role in packaging our technology into exceptional products that enhance generative AI experiences through deeper personalization via reinforcement learning. It is essential that our technology remains transparent, addressing the real challenges faced by companies without imposing additional complexities.
Your responsibilities will encompass all DevOps aspects, from systematic deployment to scaling production databases and supporting internal workloads. Expect to tackle challenges like coordinating complex GPU infrastructure and managing the storage of user interactions, which can reach trillions of records, all while ensuring robustness.
We seek passionate individuals who are self-motivated and eager to contribute to a highly technical product that emphasizes robustness, accessibility, and responsiveness. Being an early member of our team means you'll have the opportunity to significantly influence our product as we expand.
This position is ideally in-person at our offices in New York or Toronto, but we are also open to fully remote candidates.

