Member of Technical Staff - Research Software Engineer
Reflection7 months ago
Responsibilities
- Design and optimize large-scale reinforcement learning training loops and data pipelines.
- Implement state-of-the-art techniques while ensuring numerical stability and computational efficiency.
- Build internal tooling for launching, monitoring, and reproducing complex experiments.
- Diagnose GPU memory issues, communication overhead, dataloader stalls, and other training-stack bottlenecks.
- Translate research prototypes into reusable, production-grade infrastructure.
- Architect and optimize distributed GPU training systems, inference systems, and core model-training infrastructure.
Requirements
- Strong software engineering skills and fluency with machine learning concepts.
- Ability to implement research papers and translate research ideas into reliable systems; a PhD is not required.
- Deep experience in at least one of distributed training and inference or data infrastructure.
- Experience working across machine learning algorithms, distributed systems, and high-performance computing.
- Strong focus on performance, numerical stability, and reproducibility.
Benefits
- Top-tier compensation and equity, with no specific base salary amount stated.
- Comprehensive medical, dental, vision, life, and disability insurance.
- Fully paid parental leave for all new parents, including adoptive and surrogate journeys.
- Financial support for family planning.
- Paid time off and relocation support.
- Daily lunch and dinner, regular off-sites, and team celebrations.
Tech Stack
Categories
About Reflection
Reflection is a New York–based, privately held research lab developing open foundational AI models and agentic coding tools for developers, enterprises, and public-sector users. The team includes former researchers from DeepMind, OpenAI, and Anthropic, and their work focuses on transparent, customizable systems that organizations can deploy with ownership and control.