AI​/ML Engineer; Model Ops​/Prompt Engineer - SME Security Clearance

Position: AI/ML Engineer (Model Ops / Prompt Engineer) - SME with Security Clearance
Title:

AI/ML Engineer (Model Ops / Prompt Engineer) - SME
Clearance: TS/SCI

Location:

Huntsville, Al
Contact:
Overview
We are seeking a Subject Matter Expert (SME) in AI/ML Engineering to drive the development, deployment, and operationalization of cutting-edge Large Language Models (LLMs) and Natural Language Processing (NLP) systems. This senior role is critical for implementing secure, high-performance MLOps practices and advanced prompt engineering in a controlled Federal Government environment.

Key Responsibilities
As an AI/ML Engineer SME, you will:

• Model Development & Tuning:
Lead the implementation, fine-tuning, and performance optimization of LLMs and NLP models using advanced frameworks like PyTorch and Hugging Face.

• Prompt & Retrieval Engineering:
Design and optimize complex Retrieval-Augmented Generation (RAG) pipelines, manage embeddings, integrate vector databases, and execute advanced prompt engineering and long-context optimization techniques to maximize model accuracy and relevance.

• MLOps Implementation:
Architect and implement end-to-end MLOps workflows, focusing on automated deployment, robust model evaluation frameworks, drift detection, versioning, and maintaining strict responsible-AI safeguards.

• Secure Deployment:
Ensure all ML systems and infrastructure adhere to stringent Federal security controls, including FedRAMP High and the Risk Management Framework (RMF).

• Performance Optimization:
Utilize high-performance inference frameworks (e.g., vLLM, Deep Speed) and manage GPU-intensive workloads to ensure low-latency, scalable model serving.

Required Qualifications & Expertise

•

Experience:

Minimum 10+ years of professional experience in AI/ML engineering.

• LLM/NLP Focus:
At least 4+ years of direct experience focused on Natural Language Processing (NLP), Large Language Models (LLMs), or advanced MLOps implementation.

• Model Framework Expertise:
Deep expertise in one or more major ML frameworks:
PyTorch, Hugging Face Transformers, vLLM, Deep Speed, or equivalent model hosting/inference frameworks.

• Retrieval Systems:
Strong background and hands-on experience in retrieval systems, generating and managing embeddings, architecting RAG pipelines, integrating vector databases, and implementing long-context optimization.

• MLOps Maturity:
Proven experience implementing and operationalizing complete MLOps workflows, including:

• Evaluation frameworks (online/offline testing).

• Model drift detection and monitoring.

• Responsible-AI safeguards and governance.

• Secure Federal Delivery:
Demonstrated experience delivering and operating ML systems within secure federal environments subject to FedRAMP High or RMF (Risk Management Framework) controls. Desired Qualifications

• Experience with AWS Sage Maker, Azure ML, or a similar managed MLOps platform.

• Publications or active contributions to the open-source NLP/LLM community.

• Active Security Clearance (Secret, TS, or TS/SCI).