Senior Machine Learning Engineer

What you'll do

• Design and deploy agentic workflows and productionize prototype AI models.
• Develop, fine-tune, and optimize models; apply compression and hardware acceleration techniques.
• Build RAG pipelines and multimodal AI systems, and optimize execution for distributed or resource-constrained environments.

What they ask for

• Active US Security clearance.
• 4+ years of experience in applied AI, ML engineering, or production AI systems.
• Deep proficiency in PyTorch, TensorFlow, or Hugging Face Transformers, and experience deploying models across cloud, edge, and mobile hardware.
• Expertise in model compression and optimization, plus experience building RAG pipelines and integrating vector databases.

Nice to have

• Experience with edge AI, federated learning, or offline inference systems.
• Understanding of public-sector AI governance and compliance; experience with distributed systems or microservices; or GPU computing, CUDA, and performance profiling.

Tools

LoRA, PEFT, PyTorch, TensorFlow, Hugging Face Transformers, Quadrant, ChromaDB, FAISS

AI focus

Production AI engineering, including agentic workflows, model fine-tuning and optimization, RAG, multimodal systems, and inference across secure, distributed, and resource-constrained environments.