About the job
Machine Learning Developer Experience Engineer
About Our Team
At Adaptive ML, we are at the forefront of AI innovation, developing a cutting-edge Reinforcement Learning Operations (RLOps) platform that empowers enterprises to specialize and deploy Large Language Models (LLMs) with tangible outcomes. Our platform provides the foundational infrastructure needed to tune, evaluate, and serve specialized models at scale, enabling the pioneering of task-specific LLM development and the execution of production-ready workflows that manage millions of requests while optimizing for both cost and performance across distributed systems.
Our dynamic team has previously contributed to the development of state-of-the-art open-access large language models. We successfully raised $20M in seed funding led by Index Ventures and ICONIQ in early 2024, and we are already operational with clients such as Manulife, AT&T, and Deloitte, spanning the travel and financial services sectors, with many more partnerships on the horizon.
About This Role
We are searching for a talented ML Developer Experience Engineer who will empower ML engineers and development teams to utilize reinforcement learning effectively, without needing extensive RL expertise. You will be responsible for creating developer-focused tools, abstractions, and workflows that simplify the training, evaluation, and deployment of RL models, making them intuitive, robust, and scalable. Your contributions will enhance our customers' ability to adopt, grow, and manage RL use cases independently.
This position plays a crucial role in our growth strategy: your work will facilitate independent scaling for our customers, minimizing friction and enabling self-service adoption throughout their organizations. You will closely collaborate with Technical Success, Product, and Engineering teams to identify common patterns, extract reusable solutions, and delineate the boundaries between tooling and product.
This position is based in Paris, New York, or Toronto.
Your Responsibilities
Design and build user-friendly SDKs, libraries, APIs, and tools that enhance RL workflows for developers and ML engineers.
Achieve a balance between simplicity and flexibility—supporting common patterns while allowing for advanced configurations and extensibility.
Collaborate with internal teams to refine core components into documented, reusable modules that drive customer success.
Engage with technical and customer success teams to identify recurring customer patterns and workflow impediments.
Translate user feedback into tooling enhancements, error messaging improvements, onboarding processes, and example references.
Maintain comprehensive documentation to support user engagement.
