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AI/ML Engineer

Frontier Technology Inc.
Posted 4 months ago, valid for 6 days
Location

Chesapeake, VA 23326, US

Salary

Competitive

Contract type

Full Time

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Sonic Summary

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  • Frontier Technology Inc. (FTI) is looking for an AI/ML Engineer with a minimum of 6 years of professional experience in developing and deploying AI/ML solutions, particularly within defense and national security contexts.
  • The role involves designing, building, and deploying advanced machine learning models and pipelines, utilizing frameworks like PyTorch and TensorFlow, as well as developing MLOps pipelines and optimizing vector databases.
  • Candidates must possess strong Python development skills and have hands-on experience with AI/ML frameworks and MLOps tools, along with the ability to integrate AI services into real-world systems.
  • U.S. citizenship and the ability to obtain a security clearance are required for this position, which emphasizes collaboration with data engineers and software developers to ensure production-ready AI models.
  • Salary details are not explicitly mentioned, but the position is remote and offers the opportunity to work on mission-focused solutions for the Department of Defense.

Overview

Frontier Technology Inc. (FTI) is seeking a hands-on AI/ML Engineer to design, build, and deploy advanced machine learning solutions supporting defense and national security missions. This role focuses on execution in oversight, ideal for an engineer who thrives in the code, enjoys building end-to-end pipelines, and takes pride in seeing their work directly impact operational systems.

 

FTI delivers mission-focused solutions to the Department of Defense/Deparmtent of War (DoD/DoW) and Intelligence Community (IC) through advanced engineering, digital transformation, and program execution expertise. We help our customers solve complex challenges and achieve mission success by integrating people, process, and technology.

Responsibilities

  • 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.

Education/Qualifications

Minimum Requirements:

  • Must be a U.S. citizen and be willing to obtain and maintain a secruity clearance, as needed.
  • 6+ years of professional experience developing and deploying AI/ML solutions in production environments.
  • Minimum of 3 years' professional experience within the Department of Defense/Department of War (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.

 Preferred Qualifications:

  • Familiarity with agentic frameworks (LangGraph, AutoGen, CrewAI, DSPy) and multi-agent reasoning.
  • Understanding of prompt engineering, retrieval quality, and grounding methods.
  • Exposure to GPU-based or edge inference environments.
  • Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related technical field.
  • Active Secret clearance preferred; ability to obtain one is required.

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