Senior AI Systems Engineer
Core
Architect, deploy, and manage critical infrastructure services for large-scale AI model training and inference to support an all-electric vertical takeoff and landing aircraft.
Role type
Senior AI Systems Engineer (ML Infrastructure)
Builds
Robust, efficient machine learning platforms and high-performance AI inference systems for aerospace applications.
Domain
Aerospace / AI Infrastructure / High-Performance Computing
Deliverable
infrastructure
Required skills
Distributed AI model training, MLOps (MLflow), Multi-cloud compute management, Kubernetes, LLM serving optimization (vLLM, SGLang), Data pipelines for AI (SQL, NoSQL, Parquet)
Preferred skills
Audio processing, speech-to-text frameworks, Automatic Speech Recognition (ASR), Aerospace/autonomous systems experience
Technologies
AWS, Nebius AI Cloud, Docker, SkyPilot, MLflow, vLLM, SGLang, Parquet
Responsibilities
Deploy and scale resilient infrastructure for distributed AI training and low-latency inference; Maintain end-to-end tooling for the AI development lifecycle; Optimize hardware utilization and manage multi-cloud compute scheduling; Partner with researchers and engineers to productionize models and debug performance bottlenecks.
Seniority
Senior, hands-on IC
