Applied Artificial Intelligence Engineer, Warp

• You have at least 5 years of experience applying AI/ML research to build and ship user-facing, production-grade products
• You possess a strong software engineering background
• You have experience in fine-tuning and deploying large language models and predictive systems
• You're adept at prompt engineering and able to craft and iterate on prompts to optimize AI outputs and agent performance
• You’re comfortable building scalable data-driven feedback loops to measure and improve model accuracy and user satisfaction
• You thrive in a fast-paced environment, prioritizing shipping high-quality improvements over pure theoretical research
• If you’re excited about this role but your past experience doesn’t align perfectly with every qualification, we encourage you to apply anyway
• Most of us are learning new skills for the first time (like our engineers learning to program Warp in Rust). You might be just the right candidate for this or other roles

Desirable

• Warp is fundamentally changing how developers interact with technology, moving from coding "by hand" to working "by prompt."
• We're hiring an Applied AI Engineer to accelerate this transformation
• You’ll be instrumental in developing innovative predictive AI features leveraging our unique user-generated content and team data
• This applied AI Engineer role emphasizes product development and implementation, distinguishing it from a purely research-oriented position
• You will be directly reporting to John Rector, our Head of Engineering
• Your work will supercharge our natural language understanding, enhance predictive accuracy for commands, and build personalized, specialized AI agents
• By continuously refining our AI-driven suggestions and agent interactions, you'll empower hundreds of thousands of developers globally to ship better software faster, significantly impacting Warp's core product
• Design, build, and deploy predictive AI features, including natural language detection, autosuggestions, and intelligent prompt recommendations
• Leverage Warp’s extensive user-generated content and team data to continuously refine AI prediction and personalization
• Drive substantial improvements in code generation quality, including code completions, diff applications, and SWEbench performance
• Implement and iterate specialized agents tailored for specific developer workflows and use cases
• Optimize AI models through fine-tuning, advanced prompt engineering, and robust, data-driven feedback loops
• Improve context retrieval systems, enabling Warp agents to retain and utilize memory effectively
• Collaborate closely with product and engineering teams, rapidly shipping iterative improvements into production
• Continuously elevate the user experience by refining interactions between developers and Warp AI