Research Engineer

Job Title: Research Engineer — Foundation Model Training & Scaling

Location: San Francisco, CA

We’re a tight‑knit group of engineers and researchers in San Francisco building frontier‑scale models from the ground up. We believe that deep understanding starts before fine‑tuning — in how models are trained, what data they see, and how training dynamics evolve. We’re obsessed with infrastructure, data curation, and the scaling laws that shape intelligence. Our culture blends hands‑on experimentation with scientific clarity and a builder’s bias toward action.

You’ll take ownership of large‑scale pre‑training pipelines: data, compute, and model optimization. That means shaping data mixtures, tuning distributed training systems, and discovering new scaling behaviors. Your work will enable the next generation of aligned and powerful models — robust from the first training step.

• Run and iterate large‑scale pre‑training experiments
• Design scalable systems for distributed compute and efficient checkpointing
• Collaborate with research scientists on training dynamics and architecture design
• Analyze performance and scaling trends, turning insights into new experiments
• Maintain a clean, reproducible experimental stack with strong metrics discipline

• Have experience training or fine‑tuning large language or vision models
• Are fluent in deep learning frameworks like PyTorch or JAX
• Understand the nuances of large‑scale data pipelines and optimization
• Enjoy blending research curiosity with operational excellence

• Compute, autonomy, and resources to do real foundational work
• A collaborative, research‑driven culture without bureaucracy
• San Francisco HQ with relocation support
• Competitive compensation, meaningful equity, and lasting technical impact

Apply for a confidential chat!