Member of Technical Staff - Research Software Engineer

About the role

The Roles at Our Mission Reflection bridge the gap between research and production by transforming cutting-edge algorithms into scalable training systems. This team owns and evolves the core infrastructure behind our training systems, focusing on reinforcement learning training infrastructure, distributed training and inference systems, experiment infrastructure, and large-scale data pipelines.

The goal is to build the engineering foundation that allows researchers to iterate quickly while training models at massive scale.

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.

What You'll Work With

• Distributed Training
• GPU parallelism (data, tensor, pipeline, expert)
• Large-scale distributed training infrastructure
• Communication optimization (NCCL, RDMA, GPU interconnects)
• FSDP / ZeRO and model sharding
• Orchestration & Runtime Systems
• Ray, Kubernetes, Slurm
• Distributed runtimes and async systems
• Containerization and sandboxing
• Frameworks
• PyTorch, JAX, Megatron-style training stacks, Triton / custom kernels
• Data Infrastructure
• Large-scale dataset curation pipelines
• Deduplication and filtering systems
• Tokenization and preprocessing
• Distributed data processing frameworks

About You

• You are a strong software engineer who speaks the language of machine learning.
• You may not have a PhD, but you know how to implement a research paper.
• You have deep experience in at least one of the following: Distributed Training & Inference or Data Infrastructure.
• You enjoy working at the boundary between: Machine learning algorithms, Distributed systems, High-performance computing.
• You care deeply about performance, numerical stability, and reproducibility.
• You thrive in high-agency environments and enjoy solving hard technical problems.

What We Offer

• 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.