Posted today
Top Secret/SCI
Unspecified
IT - Database
Huntsville, AL (On-Site/Office)
Title: AI/ML Engineer (Model Ops / Prompt Engineer) - SME
Clearance: TS/SCI
Location: Huntsville, Al
Contact: Cdinnocenti@altaits.com
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 HuggingFace.
• 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, DeepSpeed) 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, HuggingFace Transformers, vLLM, DeepSpeed, 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 SageMaker, 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).
Clearance: TS/SCI
Location: Huntsville, Al
Contact: Cdinnocenti@altaits.com
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 HuggingFace.
• 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, DeepSpeed) 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, HuggingFace Transformers, vLLM, DeepSpeed, 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 SageMaker, 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).
group id: COMPHLP
