AI Engineer

About the job

Responsibilities

• Train, fine-tune, and deploy state-of-the-art multimodal models for real-world tasks.
• Design and implement evaluation frameworks to measure model performance and guide iteration.
• Build and scale data flywheels for continuous model improvement.
• Develop systems for live learning, feedback incorporation, and continuous model adaptation.
• Implement techniques like negative mining to harden models against edge cases.
• Own the full model lifecycle from experimentation to monitoring.
• Collaborate with engineering and product teams to integrate models into systems.

Requirements

• Hands-on experience with modern foundation models (LLMs, multimodal models) in production.
• Strong intuition for model behavior, evaluation, and failure modes.
• Experience with fine-tuning, training pipelines, and dataset construction.
• Familiarity with techniques like RLHF, synthetic data generation, or active learning.
• Comfort working with Python-based ML stacks and Typescript-based production systems.
• Bias toward action, running experiments, measuring results, and iterating quickly.
• Ownership mindset, caring about outcomes and ensuring systems work in the real world.

Benefits

• Competitive compensation
• Significant equity upside potential
• Medical, dental, and vision coverage
• In-person collaboration with a talented, experienced founding team