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$150,000 – $350,000
Listed on Modal’s own careers site. You apply with them directly — we never stand between you and the employer.
What this role is
Modal is seeking a research scientist to develop post-training methods and infrastructure for large language models, combining theoretical advances with practical deployment at scale. The role suits researchers with a track record in reinforcement learning and foundation models who want to bridge academic research and production systems.
Our summary, not Modal’s wording. The full posting is on their site.
Skills this role names
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What they ask for
Required
- Track record in reinforcement learning, machine learning, or foundation models
- Experience with large-scale model training and inference
- Ability to translate research into product impact
- Collaborative work across research and engineering teams
Nice to have
- PhD in computer science, machine learning, or related field
- Experience with multi-node GPU clusters and distributed systems
- First-author publications at top venues (NeurIPS, ICML, ICLR, CoRL, CVPR, UAI, JMLR, TMLR)
- Work on long-context or long-horizon tasks
- Expertise in inference-time efficiency and robustness