Research Engineer
Magic is an AI research and engineering company building frontier code models to automate software engineering and research.
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 train, evaluate, and serve large AI models and inference-time compute techniques. You will optimize inference throughput, contribute to research and production frameworks, train large models on GPU clusters, curate post-training data, build data pipelines and crawlers, and prototype model architectures.
Requirements
- Software engineering
- Knowledge of deep learning literature
- Experience with pre-training and post-training of LLMs
- Ability to develop and evaluate research ideas
- Experience with large distributed systems
- Ability to handle large ETL workloads
Responsibilities
- Optimize inference throughput for novel model architectures
- Contribute to research and production frameworks
- Train trillion-parameter models on large GPU clusters
- Curate post-training datasets
- Build internet-scale data pipelines and crawlers
- Design, prototype, and optimize model architectures
- Contribute to research on long-context models, inference-time compute, and reinforcement learning
Benefits
- Equity
- 401(k) plan with 6% salary matching
- Health insurance
- Dental insurance
- Vision insurance
- Unlimited paid time off
- Visa sponsorship
- Relocation stipend