AI Engineer

• Enhance AI Pipeline Accuracy: Improve our data ingestion and processing pipeline to deliver more accurate responses and sophisticated agentic behaviors in production applications.
• GPU-Optimized Model Deployment: Deploy and optimize AI models on high-performance GPU infrastructure using our Trident architecture, ensuring efficient training, inference, and scaling.
• Production MLOps: Build and maintain end-to-end MLOps pipelines including RAG systems, model distillation, fine-tuning workflows, training orchestration, and production inference deployment.
• Data Model Engineering: Design and implement robust data models and processing workflows that power our AI persona capabilities.
• Infrastructure & DevOps: Create production-grade CI/CD pipelines, containerization (Docker), comprehensive logging systems, and monitoring for AI model performance.
• Real Production Deployment: Take AI systems from development through production deployment, focusing on reliability, performance, and operational excellence.

• Python (primary language for AI/ML work)
• Strong proficiency in C++, Java, or C# for performance-critical components
• Data modeling and processing at production scale

AI/ML Production Stack:

• RAG Pipeline development and optimization
• MLOps workflows: training, inference, model lifecycle management
• Model distillation and fine-tuning techniques for production deployment
• Experience deploying models to GPU infrastructure (Trident or similar architectures)

Production Engineering:

• CI/CD pipeline creation and management
• Docker containerization and microservices architecture
• Production logging, monitoring, and observability
• Experience scaling AI systems in real production environments

What We DO Want

• 3-5 years of production AI/ML engineering experience
• Engineers from mid-sized companies who have successfully deployed AI systems at scale
• Proven track record of building, deploying, and maintaining ML systems in production
• Experience optimizing AI systems for performance, cost, and reliability
• Strong system design and architecture skills for scalable AI applications

Sample Projects You'll Own

• Optimize our RAG pipeline for improved accuracy and response quality
• Deploy and scale transformer models on our Trident GPU architecture
• Build MLOps workflows for continuous model training and deployment
• Design data processing systems for multi-modal AI persona training
• Create monitoring and alerting systems for production AI model performance