Applied AI Engineer

Overview

Build and productionize AI features that turn model capabilities into reliable user-facing behavior. Own problems across machine learning, systems, infrastructure, and product.

What you'll do

• Build and ship AI features from models through systems to user experience.
• Design and iterate on prompts, tools, memory, and agent workflows.
• Convert model outputs into structured and predictable behaviors.
• Debug issues across models, orchestration, infrastructure, and UX.
• Optimize systems for latency, cost, and production reliability.
• Develop evaluation frameworks for real-world performance.
• Work with product and engineering teams to translate ambiguous problems into working systems.

What you'll need

• Strong foundations in machine learning and modern neural network architectures.
• Hands-on experience training, fine-tuning, or deploying ML models.
• Ability to write clean, production-quality code.
• Experience with Python.
• Experience with PyTorch or JAX.
• Familiarity with LLMs, inference serving, and vector databases.
• Strong problem-solving skills in ambiguous, fast-moving environments.

Details

• Location: United States.
• Interviews may be conducted virtually and/or onsite.