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We’re looking for Founding AI Engineers who will shape how we fine-tune, serve, and evaluate LLMs and frontier models in production - and help define what it means to build a truly lovable AI product.
Job Responsibility:
Train, tune, and scale frontier LLMs that power lovable products
Own training pipelines for LLMs, from data curation to evaluation and deployment
Fine-tune models on high-quality, domain-specific data (code, natural language, product usage signals)
Work closely with product engineers to integrate models into real user-facing features
Build retrieval pipelines, evaluation frameworks, and experimentation tools
Push the limits of what’s possible with current/upcoming open models, and help define what we should train next
Requirements:
Led or contributed to cutting-edge LLM research at top AI labs / globally leading tech startups
Trained and fine-tuned LLMs on large-scale code, language, or multimodal datasets
Deep understanding of transformer architectures, attention mechanisms, and model optimization
Shipped ML systems in production, with real users and real uptime
Built fast, production-level systems while maintaining strong practices around reproducibility, monitoring, and model performance
You hold somewhat strong opinions about model safety, latency and helpfulness, but aren’t afraid to experiment