FTI - Frontier Technology Inc.

AI/ML Engineer

FTI - Frontier Technology Inc.

full-time

Posted on:

Location Type: Hybrid

Location: Raleigh • North Carolina • United States

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Tech Stack

PythonPyTorchScikit-LearnTensorflow

About the role

  • Design, develop, and deploy AI/ML models and pipelines that meet mission and performance objectives
  • Build, train, and fine-tune models using frameworks such as PyTorch, TensorFlow, scikit-learn, Hugging Face, and LangChain
  • Develop and operationalize MLOps pipelines (MLflow, Kubeflow, DVC, or custom training/inference orchestration)
  • Implement and optimize vector databases (Milvus, Pinecone, Chroma, FAISS) and retrieval architectures (RAG, graph, hybrid)
  • Write clean, efficient Python code for data ingestion, feature engineering, embeddings, and inference services
  • Experiment with fine-tuning and optimization of LLMs and task-specific models (LoRA, QLoRA, PEFT)
  • Contribute to agent-based applications using frameworks like LangGraph, AutoGen, CrewAI, or DSPy
  • Integrate AI services into real-world systems via APIs, event-driven workflows, or UI copilots
  • Collaborate with data engineers, software developers, and mission analysts to ensure AI models are production-ready and aligned with customer needs
  • Participate in peer reviews, contribute to shared repositories, and document models and experiments for reproducibility.

Requirements

  • Must be a U.S. citizen and be willing to obtain and maintain a secruity clearance
  • 6-10+ years of professional experience developing and deploying AI/ML solutions in production environments
  • Professional experience within the Department of Defense (DoD/DoW) AI assurance, security, and deployment environments
  • Strong Python development skills with hands-on experience building AI/ML solutions
  • Direct experience with ML frameworks such as PyTorch, TensorFlow, scikit-learn, Hugging Face, or LangChain
  • Proven ability to build and deploy MLOps pipelines using MLflow, Kubeflow, DVC, or equivalent
  • Working knowledge of vector databases (Milvus, Pinecone, Chroma, FAISS) and retrieval-based architectures (RAG, hybrid, graph)
  • Professional experience fine-tuning and evaluating LLMs or smaller task-specific models using LoRA, QLoRA, or PEFT
  • Professional experience integrating AI capabilities into production systems or mission applications.
Benefits
  • Competitive salary
  • Health insurance
  • Paid time off
  • Flexible work arrangements
Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools
AI/ML modelsMLOps pipelinesPythonfine-tuningmodel optimizationdata ingestionfeature engineeringembeddingsinference servicesagent-based applications
Soft Skills
collaborationpeer reviewsdocumentationcommunication
Certifications
security clearance