Performance Engineer, Rust

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 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 are already live in production with customers including Manulife, AT&T, and Deloitte across travel and financial services — with much more to be announced soon.

We are looking for a Performance Engineer to join our core engineering team and build the foundational technology powering Adaptive ML. This role sits at the heart of our systems infrastructure, combining high-performance software engineering with the rigour required to operate at scale in production AI environments.

You will write high-quality Rust, diagnose complex bugs at the hardware–software boundary, and contribute directly to the technical direction of the product. We are a distributed, asynchronous-first team that values depth, ownership, and clear communication.

• Build the foundational technology powering Adaptive ML, with a relentless focus on high-performance software engineering;

• Write production-grade Rust, combining correctness, performance, and robustness across large-scale distributed systems;

• Identify and resolve complex bugs at the intersection of software and hardware correctness in distributed environments.

• Contribute to the product roadmap by identifying promising trends and surfacing high-impact technical findings;

• Engage with research developments in generative AI and reinforcement learning to inform engineering decisions.

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

• Partner with teammates across engineering, research, and product to deliver robust, scalable solutions.

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.

• A M.Sc. or Ph.D. in Computer Science, or equivalent demonstrated experience in software engineering, preferably with a focus on machine learning;

• Strong Rust skills, or a clear inclination to develop them — especially in distributed systems where performance is key;

• Contributions to relevant open-source projects, such as efficient model implementations or reinforcement learning libraries;

• Passionate about the future of generative AI, and eager to build foundational technology that helps machines deliver more singular experiences.