Gallatin AI
Machine Learning Operations (MLOps) Engineer
About this role
Gallatin seeks an MLOps Engineer to build production infrastructure for AI/ML systems supporting U.S. national security logistics. You'll own the full pipeline from model training to deployed capability across cloud and on-premises environments, including air-gapped and restricted networks.
What you'll do
- Design and operate model training, fine-tuning, and inference infrastructure on AWS (SageMaker, EKS) and on-premises GPU hardware
- Build LLM serving stacks (vLLM, quantization, batching) with local-first deployment for degraded-mode resilience
- Develop CI/CD pipelines with versioned datasets, model registry, promotion gates, and reliable rollback mechanisms
- Create evaluation harnesses with regression testing, LLM-as-judge systems, and adversarial datasets; instrument production for drift and silent failures
- Manage data ingestion, embedding pipelines, feature freshness, and human-in-the-loop confidence routing and feedback systems
- Deploy and operate ML systems in IL5/IL6 environments; support ATO/continuous authorization with security control evidence (NIST, CMMC, FIPS 140-3, RMF/eMASS)
What they're looking for
- MLOps and ML platform engineering (5+ years production experience)
- Python, Kubernetes, containerization, and infrastructure as code
- AWS ML services (SageMaker, EKS) and cloud ML infrastructure
- GPU scheduling, memory optimization, and cost management
- IL5/IL6 and air-gapped/restricted-network deployment operations
- LLM inference serving and optimization (vLLM, quantization, KV-cache sizing)
- Production monitoring, observability, and incident response
- Security compliance frameworks (NIST SP 800-171/53, CMMC, FIPS 140-3, RMF/eMASS)
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Gallatin AI
Gallatin AI builds AI-powered logistics optimization systems for national security and defense operations, focusing on feasibility validation, allocation algorithms, routing networks, and supply chain decision-making. The company is hiring AI Engineers, Backend Engineers, and Infrastructure Engineers to design scalable, secure systems that ensure military logistics plans are compliant, auditable, and operationally robust.
View all jobs at Gallatin AILikely interview questions
- Walk us through a time you deployed an LLM or ML system to production and encountered an unexpected failure—how did you diagnose and resolve it?
- Describe your experience setting up and optimizing GPU infrastructure for training and inference; how do you approach memory sizing and cost trade-offs?