Member of Technical Staff Pre-training Systems
MagicVisit Magic website
Magic is an AI research and engineering company building frontier code models to automate software engineering and research.
San Francisco, United States
Funding history
About Magic
Magic AI, Inc. develops long-context foundation models and agentic systems for software engineering, combining pre-training, reinforcement learning, ultra-long context, and inference-time compute in pursuit of safe AGI.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will design and operate distributed infrastructure for large-scale model training. You will scale training across GPU clusters, optimize communication and synchronization, improve checkpointing and recovery, eliminate system bottlenecks, and improve reproducibility and hardware utilization.
Requirements
- Strong software engineering and distributed systems fundamentals
- Experience training large models in multi-node GPU environments
- Deep understanding of parallelism strategies and performance trade-offs
- Experience debugging cross-layer issues in production ML systems
- Ability to operate critical infrastructure
- Track record of improving performance or reliability of large-scale systems
Responsibilities
- Scale distributed training across large GPU clusters using data, tensor, and pipeline parallelism
- Optimize communication patterns and gradient synchronization
- Improve checkpointing, fault tolerance, and job recovery systems
- Profile and eliminate performance bottlenecks across compute, networking, and storage
- Improve experiment reproducibility and orchestration workflows
- Increase hardware utilization and training throughput
- Collaborate with Kernels and Research to align model architecture with systems realities
Benefits
- Equity as a significant part of total compensation
- 401(k) plan with 6% salary matching
- Health, dental, and vision insurance for employees and dependents
- Unlimited paid time off
- Visa sponsorship
- Relocation stipend to San Francisco