Staff MLOps Engineer
Core
Architect the operational backbone for a new Data Inference AI Pipeline serving satellite and AI-powered grid resilience products for electric utilities.
Role type
Staff MLOps Engineer (hands-on IC)
Builds
Scalable, cost-optimized, resilient model deployment and inference infrastructure on AWS SageMaker
Domain
Energy/Utilities + Cloud Infrastructure (AWS)
Deliverable
production ML models
Required skills
AWS SageMaker, Kubernetes, Docker, CI/CD for ML, autoscaling, cost optimization, disaster recovery, model monitoring, technical leadership
Preferred skills
Large imagery/video/3D sensor data pipelines, multimodal data, MLOps from scratch, model drift detection, GPU cost optimization, regulated enterprise domains
Technologies
AWS SageMaker, Kubernetes, Docker, Inferentia/Trainium
Responsibilities
Own end-to-end model deployment pipelines (packaging, versioning, rollout, rollback); Design inference infrastructure for scalability and elasticity; Instrument and optimize cost-per-inference metrics; Design failover and disaster recovery procedures; Partner with Data Science and Web Application teams to ship models; Serve as technical authority on MLOps practices
Seniority
Staff, hands-on IC