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General Dynamics Information Technology

Builds and runs technology for government agencies

Principal AI Platform and Model Operations Engineer

Applied Machine LearningPosted on Nov 5
Full-timeChantilly, VA, USA$161.5k - $218.5k

About the Job

Requirements

  • A bachelor's degree in computer science, Software Engineering, Machine Learning, Information Technology, or a related field, or approved equivalent experience.
  • At least 8 years of platform, DevSecOps, site reliability engineering, machine learning engineering, or cloud engineering experience, including at least 3 years supporting production AI/ML platforms.
  • Hands-on experience deploying and operating local model-serving platforms such as vLLM, TGI, Triton, TensorRT-LLM, llama.cpp, Ollama, ONNX Runtime, or comparable technologies.
  • Strong skills in Linux, containers, Kubernetes/OpenShift, networking, storage, GPUs, identity, secrets, and infrastructure automation.
  • Experience with model/artifact registries, experiment tracking, release management, continuous integration/continuous delivery, internal package/container repositories, and disconnected dependency management.
  • Ability to size inference capacity using model precision, VRAM, context length, concurrency, throughput, latency, and availability requirements.
  • Strong Python and automation proficiency, plus experience with Terraform, Ansible, Helm, GitLab CI/Jenkins, or comparable tooling.
  • Working knowledge of RMF/STIG, software supply-chain security, software bills of materials, vulnerability management, logging/audit, and classified data handling.
  • Demonstrated technical leadership, incident judgment, cross-team coordination, mentoring, and clear documentation.
  • Must hold an active Top Secret/Sensitive Compartmented Information clearance with polygraph and be a U.S. citizen.

Responsibilities

  • Design and operate AI/ML platform services for local model serving, orchestration, model and artifact registries, experiment/evaluation tracking, feature or retrieval assets, and deployment automation.
  • Build controlled import and release workflows for model weights, containers, Python packages, libraries, prompts, datasets, and vulnerability updates in disconnected environments.
  • Implement provenance, checksums/signing, software bills of materials, malware/vulnerability scans, license review, allowlists, approvals, staged validation, and rollback for AI artifacts.
  • Deploy and tune inference services using approved serving stacks; manage batching, concurrency, memory, quantization, autoscaling where available, queueing, resilience, and graceful degradation.
  • Establish versioning and release relationships among models, tokenizers, prompts, retrieval indexes, embedding models, configurations, evaluation sets, applications, and infrastructure.
  • Develop GPU/CPU/storage/network capacity models and advise on hardware options, consolidation, scheduling, and cost/performance trade-offs.
  • Implement health, latency, throughput, saturation, failure, quality, drift, and usage telemetry integrated with enterprise observability and ServiceNow.
  • Define backup/recovery, continuity, patching, vulnerability treatment, certificate/secret rotation, and incident procedures for AI platform services.
  • Partner with AI Assurance and Security to enforce use-case gates, evaluation thresholds, audit, data restrictions, and release evidence.
  • Lead technical reviews, troubleshoot production AI platform incidents, mentor engineers, and document reusable platform patterns.

Desired Qualifications

  • Experience with PyTorch, Hugging Face, MLflow, Kubeflow, Ray, NVIDIA GPU tooling, CUDA, or enterprise AI platform products.
  • Experience operating A100, H100, L40S, or comparable accelerators and performing quantization/optimization.
  • Experience with Azure Government, AWS GovCloud, C2S-equivalent, or on-premises platform delivery.
  • Role-relevant CKA/CKS, current Red Hat platform engineering credentials, Microsoft Certified: DevOps Engineer Expert, or relevant Terraform, NVIDIA, or ML-platform credentials.
  • Experience integrating model-quality/evaluation signals with deployment gates and production monitoring.

About the Company

General Dynamics Information Technology

Builds and runs technology for government agencies

GDIT builds and runs technology systems for U.S. government agencies, including defense, intelligence and civilian organizations. Its work spans cloud infrastructure, cybersecurity and software development, with tools tailored to sensitive missions and large agency operations. The company combines its own reusable technology solutions with commercial products, then earns revenue through contracts to design, integrate, modernize and operate customer systems, including support for both classified and unclassified networks. It also supplies technical expertise and daily operational support, and is a business unit of General Dynamics headquartered in Falls Church, Virginia.

Company size
10,001+
Company stage
Not listed
Total funding
Not listed
Headquarters
Falls Church, VA
Founded
1999

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