Member of Technical Staff, Post-Training, RL Infra
About The Position
Mirendil is a tech-first company focused on solving core bottlenecks that unlock step-change acceleration across science and technology. Our first goal is to democratize frontier AI R&D across scientific disciplines. We believe accelerating scientific discovery is one of the most powerful ways to improve the future of humanity, and that AI will play a central role in making that possible. We are building a frontier AI research company and training our own models end-to-end. Our work spans areas such as model training, reinforcement learning, reasoning systems, and infrastructure for large-scale experiments. Our team includes researchers and engineers from Anthropic, Google DeepMind, xAI, OpenAI, Microsoft, Apple, and MIT.
Requirements
- Engineers to help build the post-training stack for frontier reasoning models
- Work to push the scale of our RL stack, whether it is novel recipe ideas, reliability, or performance
- Excited about building the infrastructure that makes frontier RL research possible at scale
Responsibilities
- Design and build reliable infrastructure for large-scale RL training
- Implement novel performance optimizations across the training stack
- Develop evaluation and benchmarking infrastructure to measure model progress, throughput, and uptime
- Build data collection and feedback pipelines that close the loop between human signal, reward modeling, and training
- Collaborate with multiple teams to rapidly iterate on RL algorithms and get experiments into production training runs
Benefits
- competitive benefits
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
