Machine Learning Operations (MLOps) Engineer

Job Description

• Build and operate MLOps infrastructure spanning AWS SageMaker/EKS, Azure-equivalent ML infrastructure, on-premises GPUs, and disconnected or air-gapped IL5/IL6 environments.
• Own model training, fine-tuning, batch inference, LLM serving optimization, CI/CD, infrastructure as code, containerization, GitOps, model registries, reproducibility, promotion gates, and rollback.
• Create evaluation, monitoring, observability, data lineage, embedding, indexing, and human-in-the-loop systems for retrieval-grounded ML and LLM applications.
• Support ATO and continuous authorization using NIST SP 800-171, NIST SP 800-53 Rev. 5, CMMC Level 2, FIPS 140-3, and RMF/eMASS controls; handle CUI and classified data.
• Requires 5+ years of MLOps, ML platform, or infrastructure engineering experience, strong Python, Kubernetes, containerization, IaC, GPU infrastructure, and production ML experience; U.S. citizenship and ability to obtain and maintain a U.S. government security clearance are required or may be required.
• Full-time role in El Segundo, CA; compensation is $80K–$210K.