The Role
A modelling residency puts you in the center of a frontier lab. You'll be embedded in real work: placed on key production and research projects and mentored directly by our modelling team. We're building our frontier innovation around efficiency, gradient-free exploration, real-time learning, and interface design. By the end of the residency, our hope is that you leave with a track record you're proud to put on your resume and experiences that meaningfully upskill you.
Responsibilities
- Innovation: Build the future of adaptive algorithms that continuously learn. Co-design algorithms that react in real-time to product signal and feedback, and explore new ways of capturing feedback that make those algorithms better
- Cross-Stack Optimization: Collaborate across software, hardware, and algorithmic domains to drive system-wide efficiency gains
- Measure What Matters: We believe the ultimate signal of value is real-world impact. The smartest algorithm is one capable of interacting with the world — that's why product signal matters so much to how we work.
Qualifications
We value impact over credentials. Above all, we're looking for great teammates who make work feel lighter and aren't afraid to go out on a limb with bold ideas. You don't need to check every box - but you do need to be adaptable.
- A degree or equivalent research/engineering experience in a computer science field.
- Genuine interest in, and at least one project touching: model efficiency, synthetic data, interfaces, real-time alignment, or algorithmic optimization
- Systems thinking — the ability to understand and optimize across the full ML stack
- Strong Python skills and experience with deep learning frameworks (PyTorch, JAX, or TensorFlow)
- Familiarity with model optimization techniques such as RLHF and fine-tuning
- You care about technical excellence and last mile impact. We value impact more than effort, and about owning outcomes end to end.