AI/ML Engineer

Frontier Technology Inc. (FTI) is seeking a highly skilled and hands-on AI/ML Engineer to design, develop, and deploy advanced machine learning solutions supporting Department of Defense (DoD) and Intelligence Community (IC) missions. This role is ideal for engineers who enjoy building end-to-end AI pipelines, developing production-grade systems, and delivering operational impact through modern AI technologies., * Design, develop, and deploy AI/ML models and pipelines to meet mission and performance objectives.

• Build, train, fine-tune, and optimize machine learning models using PyTorch, TensorFlow, Scikit-learn, Hugging Face, and LangChain.
• Develop and operationalize MLOps pipelines using MLflow, Kubeflow, DVC, or equivalent orchestration frameworks.
• Implement and optimize Vector Databases including:
• Milvus
• Pinecone
• Chroma
• FAISS
• Develop retrieval architectures utilizing:
• Retrieval-Augmented Generation (RAG)
• Graph-based retrieval
• Hybrid retrieval models
• Write efficient Python code for:
• Data ingestion
• Feature engineering
• Embeddings generation
• Inference services
• Fine-tune and optimize LLMs and task-specific models using:
• LoRA
• QLoRA
• PEFT
• Contribute to agent-based AI applications using:
• LangGraph
• AutoGen
• CrewAI
• DSPy
• Integrate AI capabilities into production systems using APIs, event-driven workflows, and UI copilots.
• Collaborate with data engineers, software developers, and mission analysts to ensure AI solutions are production-ready.
• Participate in peer reviews, maintain shared repositories, and document experiments and models for reproducibility.

• 6 10+ years of professional experience developing and deploying AI/ML solutions in production environments.
• Minimum 3 years of experience within DoD/Defense AI assurance, security, and deployment environments.
• Strong programming expertise in Python.
• Hands-on experience with:
• PyTorch
• TensorFlow
• Scikit-learn
• Hugging Face
• LangChain
• Experience building and deploying MLOps pipelines using:
• MLflow
• Kubeflow
• DVC
• Equivalent orchestration frameworks
• Strong knowledge of Vector Databases:
• Milvus
• Pinecone
• Chroma
• FAISS
• Experience with retrieval architectures:
• RAG
• Hybrid retrieval
• Graph-based retrieval
• Hands-on experience fine-tuning and evaluating LLMs using:
• LoRA
• QLoRA
• PEFT
• Experience integrating AI capabilities into production applications and mission systems.
• Strong understanding of AI deployment and production environments.

Preferred Qualifications:

• Familiarity with Agentic AI frameworks:
• LangGraph
• AutoGen
• CrewAI
• DSPy
• Experience with multi-agent reasoning systems.
• Understanding of:
• Prompt Engineering
• Retrieval Quality
• Grounding Techniques

Exposure to:

• GPU-based inference environments
• Edge AI deployments
• Bachelor’s or Master’s degree in:
• Computer Science
• Engineering
• Data Science
• Related technical disciplines
• Active Secret Clearance preferred.
• Ability to obtain security clearance is required.

Soft Skills:

• Strong analytical and problem-solving skills.
• Excellent written and verbal communication abilities.
• Ability to collaborate effectively with cross-functional teams.
• Strong documentation and knowledge-sharing practices.
• Ability to work in mission-critical and highly secure environments.
• Self-driven mindset with strong ownership and accountability.
• Ability to thrive in fast-paced engineering environments.
• Additional Notes
• Opportunity to support Department of Defense (DoD) and Intelligence Community (IC) initiatives.
• Focus on production-grade AI/ML systems and operational mission impact.
• Exposure to cutting-edge technologies including:
• LLMs
• RAG Architectures
• Vector Databases
• Agentic AI
• MLOps
• Multi-Agent Systems
• Engineers with security clearance backgrounds are highly preferred.
• Ability to obtain an Active Secret Clearance is mandatory.

Mandatory Skills:

• Python
• PyTorch
• TensorFlow
• Scikit-learn
• Hugging Face
• LangChain
• MLOps
• MLflow
• Kubeflow
• DVC
• Vector Databases
• Milvus
• Pinecone
• Chroma
• FAISS
• Retrieval-Augmented Generation (RAG)
• LoRA
• QLoRA
• PEFT
• Large Language Models (LLMs)
• AI Model Fine-Tuning
• Production AI Deployment
• Agentic AI Frameworks
• LangGraph
• AutoGen
• CrewAI
• DSPy
• Prompt Engineering
• Multi-Agent Systems
• DoD Environment Experience
• Defense AI Security
• AI Assurance
• Secret Clearance Eligibility