Design and optimize high-performance microarchitectures for machine learning applications in autonomous vehicles, collaborating with researchers and verification teams.
Application Software Engineer, Applied AI
🕒 3 days ago
AI SystemsLarge Language ModelsAgentic SystemsFull Stack Development
📜 Description
- Develop highly reliable software solutions used across SpaceX, including AI-powered applications that accelerate production, flight, and Starlink operations
- Create new applications that improve how SpaceX operates by incorporating modern large language models, agentic systems, and other AI capabilities
- Own the full lifecycle of Applied AI systems: design, evaluation, deployment, monitoring, and iteration from prototype to production
- Deep dive into users' problems to uncover high-leverage AI opportunities and deliver efficient, production-grade solutions
- Architect production systems for agentic workflows, tool-use, multi-agent orchestration, advanced retrieval, and long-context applications that prioritize reliability, safety, and responsible deployment
- Build and maintain rigorous evaluation frameworks and production observability/monitoring for AI quality, safety, latency, and cost
🛠️ Requirements
- Bachelor's degree in computer science, engineering, math, or scientific discipline; OR 2+ years of professional experience building software in lieu of a degree
- 1+ years of experience in full stack development
- Hands-on experience evaluating, deploying, and integrating AI models into production systems
- Proven track record of delivering (or significantly contributing to) end-to-end AI products or production AI-powered features
- Proven track record of shipping real-world AI products from prototype through production deployment and iteration
- Deep hands-on experience with modern LLM techniques: agentic systems, tool-use / function calling, multi-agent orchestration, advanced retrieval architectures, fine-tuning, and structured outputs
- Experience building production evaluation systems (LLM-as-judge, automated eval harnesses, A/B testing, red-teaming) and AI observability/monitoring (tracing, quality metrics, safety, cost)
- Experience designing and implementing production architecture for AI-powered applications with strong emphasis on reliability, safety, and responsible deployment
- Previous experience in AI product design, development, integration, testing, and productionization
- Strong software engineering foundation with expertise in designing production systems (including AI-powered and system-to-system architectures) and a track record of writing clean, maintainable code
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