AI Research Engineer

Alexander Chapman; San Francisco (CA); On-site; USD 150,000 - 230,000; Full time

Job summary

Alexander Chapman is seeking an AI Research Engineer to help build and improve production LLM systems powering a highly personalized AI product.

You will collaborate with product, research, and engineering to ship new AI capabilities, ensuring rigorous evaluation, safety, and robust deployment in a fast-paced environment in San Francisco.

Qualifications

• LLMs, fine-tuning/post-training, reinforcement learning, model evaluation, and production ML systems.

Responsibilities

• Fine-tune and improve LLMs using training data curation, reinforcement learning, and other post-training techniques.
• Build robust evaluation systems using LLM-as-a-judge, human feedback, safety checks, and automated testing.
• Own models from research to production, including training, deployment, monitoring, reliability, and iteration.
• Run experiments to improve model quality, reasoning, personalization, and user outcomes.
• Improve AI safety, alignment, and guardrails alongside domain experts.
• Work closely with product, research, and engineering to ship new AI capabilities.

Skills

LLMs

Fine-tuning

Reinforcement learning

Model evaluation

Production ML systems

Job description

We’re looking for an AI Research Engineer to help build and improve production LLM systems powering a highly personalized AI product.

What you’ll do

• Fine-tune and improve LLMs using training data curation, reinforcement learning, and other post-training techniques
• Build robust evaluation systems using LLM-as-a-judge, human feedback, safety checks, and automated testing
• Own models from research to production, including training, deployment, monitoring, reliability, and iteration
• Run experiments to improve model quality, reasoning, personalization, and user outcomes
• Improve AI safety, alignment, and guardrails alongside domain experts
• Work closely with product, research, and engineering to ship new AI capabilities

What we’re looking for

Strong experience with LLMs, fine-tuning/post-training, reinforcement learning, model evaluation, and production ML systems, with the ability to take ideas from research through deployment.