Member of Technical Staff Research Post Training
ModalVisit Modal website
Modal Labs, Inc. operates Modal, a serverless cloud and AI infrastructure platform for developers running inference, training, batch processing, and isolated sandboxes.
New York City, United States
Funding history
About Modal
Modal provides code-first, elastic CPU/GPU compute infrastructure for AI workloads, including model inference, fine-tuning and training, large-scale batch jobs, and secure ephemeral execution environments.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will research and develop methods for post-training, large-scale model optimization, and inference. You will improve long-context and long-horizon model capabilities, inference efficiency, reliability, and robustness for real-world deployments.
Requirements
- Research accomplishments in reinforcement learning, machine learning, foundation models, or related fields
- Experience with large-scale training and inference infrastructure
- Experience with distributed systems and multi-node GPU clusters
- Experience developing, training, optimizing, or deploying large-scale models
- Research publications at leading venues
- Ability to work effectively across research and engineering
Responsibilities
- Develop techniques for large-scale model training, optimization, and inference
- Extend models to long-context and long-horizon tasks
- Improve inference efficiency, reliability, and robustness
Benefits
- Equity