Deployment DevOps Engineer

Adaptive ML is a frontier AI startup building a Reinforcement Learning Operations (RLOps) platform that enables enterprises to specialize and deploy LLMs into production with measurable impact.

We provide the core infrastructure to tune, evaluate, and serve specialized models at scale — pioneering task-specific LLM development and running production-ready workflows that serve millions of requests while optimizing for both cost and performance across distributed systems.

Our tightly-knit team was previously involved in the creation of state-of-the-art open-access large language models. We raised a $20M seed led by Index Ventures and ICONIQ in early 2024, and we're already live in production with customers including Manulife, AT&T, Deloitte, across travel and financial services — with much more to be announced soon.

Our Product Staff is responsible for packaging the technology we build and turning it into an exceptional product that directly answers pain points companies encounter in their generative AI deployments. We strive to build a high-quality, intuitive, and robust experience for our customers.

As a DevOps Engineer in our Product Staff, you will help package our technology and turn it into an exceptional product. Our products help companies build more singular generative AI experience, by enabling deeper personalization with reinforcement learning. Importantly, the technology in our products has to be transparent, and to directly answer pain points companies face—not add another layer of inextricable complexity. We place tremendous importance on the quality of our product, with particular emphasis on ease-of-deployment/use, robustness, and scalability, which can only be achieved with tremendous care on the devops side.

You will work on all DevOps aspects of our product, from systematic deployment to scaling production databases, as well as support internal workloads. Challenges you may face are likely to arise from coordinating complex GPU infrastructure and scaling the storage of user interactions to trillions of records in a robust manner. We are looking for self-driven, intense individuals, interested in contributing to a highly-technical product with challenges regarding robustness, accessibility, and responsiveness. As this is an early role, you can expect to be able to directly shape our product team as we grow.

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  Build systematic K8s workflows to deploy our product, either client-side on a variety of infrastructures, or internally for our cloud platform;

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  you'll work closely with sales and customer success to assist product deployment, pre and post sales (POC, demos, production), both on-prem, in cloud and in our SaaS.

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  you'll be part of our first line of support for customer escalation, including bugs, security escalations, special events support (scale-outs, large workshops, load tests)

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  Contribute to deployment support, in particular on North America time zones. This involves both personally joining customer calls to assist onboarding and troubleshooting, but also leading and contributing to our support mechanisms such as ticket triaging and oncall process.

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  Contribute to our product roadmap, by coordinating between the needs of the Commercial Staff and latest developments from our Technical Staff;

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  Report clearly on your work to a distributed collaborative team, with a bias for asynchronous written communication.

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  Comfort and curiosity with hybrid and on-premises architectures, including administration of long-running bare-metal infrastructure, Linux networking, and on-premises devsecops.

The background below is only suggestive of a few pointers we believe could be relevant; we welcome applications from candidates with diverse backgrounds, do not hesitate to get in touch if you think you could be a great fit even if the below doesn't fully describe you.