Lead Machine Learning Engineer

Focusing on the full lifecycle of AI features, the full-time Lead Machine Learning Engineer will optimize inference and performance for document intelligence and RAG pipelines, collaborating with clients to develop high-performance AI architectures in a remote environment. Key responsibilities: Optimize inference and build production LLM serving to maximize throughput and minimize latency Profile and accelerate training runs to identify and resolve bottlenecks Deploy and operate multiple models within shared GPU clusters, ensuring efficient resource utilization Required qualifications: Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field 5+ years of experience in ML/AI engineering, particularly in performance and infrastructure Proven experience deploying and optimizing models in a production environment Strong understanding of GPU architecture and profiling tools for training and inference Experience with Kubernetes (GKE) for deploying and autoscaling models on Google Cloud