AI Systems Engineer
Hybrid – Alexandria, VA
Active or Eligible U.S. Security Clearance Required
About the Role
We’re looking for an AI Systems Engineer to support Public Sector initiatives by building secure, distributed, and high-performance AI systems. You’ll turn research models into production-ready solutions that run across cloud, edge, and constrained environments—optimizing everything from model performance to low-level GPU acceleration.
What You’ll Do
- Convert prototype models into scalable, robust AI systems.
- Optimize models using PyTorch, TensorFlow, or Hugging Face.
- Apply quantization, pruning, distillation, and hardware acceleration.
- Build LoRA / PEFT workflows and on-device inference pipelines.
- Develop RAG systems integrated with vector databases (FAISS, Milvus, Pinecone).
- Support multimodal (text / vision / audio) model deployments.
- Generate synthetic data using GANs or diffusion models.
- Write performance-critical code in C / C++ / Rust with GPU optimization.
- Engineer for distributed, edge, and offline environments.
- Collaborate with Infrastructure, MLOps, and Security teams.
What You Bring
Active or eligible U.S. security clearance.5+ years in applied AI, ML engineering, or AI systems development.Strong experience with major ML frameworks and cloud / edge deployment.Expertise in model compression, GPU computing, and CUDA.Experience with RAG pipelines, vector databases, multimodal systems, and synthetic data.Strong C / C++ / Rust and systems-level programming skills.Solid algorithmic and distributed-systems problem-solving ability.Preferred
Experience with edge AI, federated learning, or offline inference.Familiarity with distributed training (DeepSpeed, Ray).Knowledge of public-sector AI governance and compliant architectures.Strong communication and documentation skills.