Member of Technical Staff - Research Software Engineer

You will architect and optimize the core training infrastructure that powers our models. This includes RL training loops, distributed GPU systems, and large-scale data pipelines. You will work closely with researchers to transform new ideas into reliable, scalable training systems.

Responsibilities

Designing and optimizing large-scale training loops and data pipelines; Implementing state-of-the-art techniques and ensuring they are numerically stable and computationally efficient; Building internal tooling for launching, monitoring, and reproducing complex experiments; Diagnosing deep bottlenecks across the training stack (GPU memory issues, communication overhead, dataloader stalls); Translating research prototypes into reusable, production-grade infrastructure

Requirements

Strong software engineer who speaks the language of machine learning; Know how to implement a research paper; Deep experience in at least one of the following: Distributed Training & Inference or Data Infrastructure; Enjoy working at the boundary between machine learning algorithms, distributed systems, and high-performance computing; Care deeply about performance, numerical stability, and reproducibility; Thrive in high-agency environments and enjoy solving hard technical problems

Benefits

Top-tier compensation: Salary and equity structured to recognize and retain our talent globally; Stock options: Everyone who joins and contributes to Reflection's success gets to share in the upside through stock options; Health & wellness: Comprehensive medical, dental, vision, and life, with an annual wellness allowance; Meals: Lunch and dinner are provided in the office daily; Life & family: 22 weeks paid parental leave for all new birthing and non-birthing parents, including adoptive and surrogate journeys; Vacation days: Unlimited paid time off in the U.S. and 30 days in the U.K.; Sponsorship support: We sponsor visas to help exceptional talent join our team and support long-term immigration pathways where applicable; Team building: We have regular off-sites, happy hours, and team celebrations