Mirendil

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 are building a frontier AI research company and training our own models end-to-end.

The Role

We are looking for an engineer to work at the intersection of research and systems on our pretraining stack. You'll contribute across the full pipeline, from data processing and model architecture to distributed training infrastructure and low-level optimization, and help determine how we scale our next generation of models. Some example areas you might work on (not limited to):

Implement and iterate on model architectures, training algorithms, and optimizer research in large-scale pretraining runs

Scale distributed training jobs across thousands of GPUs

Optimize training throughput for novel attention mechanisms, architecture variants, and compute efficiency improvements

Design and build large-scale data pipelines for efficient model consumption and dataset curation

Run and analyze scientific experiments to advance understanding of how architecture and data choices affect model capabilities

If you're excited about working across research and engineering to push the frontier of what large models can do, we'd love to hear from you.

We offer a base salary of $300,000–$400,000 USD and a meaningful equity grant, depending on experience and background, along with competitive benefits.