LaunchCode
Agentic AI Machine Learning Engineer - Secret Clearance
LaunchCode, Saint Louis, Missouri, United States, 63146
Overview
Job Title: Agentic AI Machine Learning Engineer - Secret Clearance Location: On-Site in Washington, D.C.; Arlington, VA; McLean, VA; St. Louis, MO; Denver, CO; Colorado Springs, CO Employment Type: Full-Time, Direct Hire (W2) Pay: $99,000.00 to $225,000.00 Responsibilities
Design, develop, and implement AI/ML systems that enhance mission effectiveness for Defense and Intelligence clients. Build and operationalize agentic AI solutions, integrating frameworks such as LangChain, LangGraph, PydanticAI, or LlamaIndex. Architect scalable and resilient ML applications for fast-moving data and evolving mission requirements. Train, deploy, and maintain production-grade models across multiple data modalities on AWS and Azure. Deploy ML solutions in containerized environments using Docker and Kubernetes. Integrate AI agents with APIs, cloud services, and databases. Apply MLOps, GitOps, and CI/CD practices to deployment, monitoring, and improvement of ML systems. Evaluate architectural tradeoffs and design service-based applications optimized for performance and scalability. Collaborate with cross-functional teams to deliver end-to-end solutions. Explore emerging AI/ML approaches, including LLMs, deep learning, and reinforcement learning. Communicate technical concepts clearly to both technical and non-technical stakeholders. Required Skills & Qualifications
3+ years of experience as an ML engineer building production-grade ML solutions, including work with LLMs, agents, or complex automation frameworks 3+ years of experience in data science or data research, training or deploying models across multiple data modalities 3+ years of experience in cloud environments (AWS and Azure) 2+ years of experience deploying and integrating production-grade ML models using Docker and Kubernetes Experience with LLMs, ML, DL, and RL Experience with AI agent frameworks such as LangChain, LangGraph, PydanticAI, or llamaindex Experience connecting agents to APIs, cloud platforms, or databases, and with MLOps, GitOps, and CI/CD tooling Experience evaluating architectural tradeoffs and designing robust service-based software for scalable use Secret clearance Bachelor’s degree Preferred Qualifications
Experience with TensorFlow, PyTorch, llama.cpp, and vLLM Experience with client engagements, project work, and business development Experience in deep learning, computer vision, NLP, or signal processing Experience deploying and managing data brokering solutions (e.g., Kafka, Red Panda, Confluent) Strong adaptability, communication, and interpersonal skills Master’s degree Job Details
Seniority level: Mid-Senior level Employment type: Full-time Job function: Engineering and Information Technology Industries: Staffing and Recruiting
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Job Title: Agentic AI Machine Learning Engineer - Secret Clearance Location: On-Site in Washington, D.C.; Arlington, VA; McLean, VA; St. Louis, MO; Denver, CO; Colorado Springs, CO Employment Type: Full-Time, Direct Hire (W2) Pay: $99,000.00 to $225,000.00 Responsibilities
Design, develop, and implement AI/ML systems that enhance mission effectiveness for Defense and Intelligence clients. Build and operationalize agentic AI solutions, integrating frameworks such as LangChain, LangGraph, PydanticAI, or LlamaIndex. Architect scalable and resilient ML applications for fast-moving data and evolving mission requirements. Train, deploy, and maintain production-grade models across multiple data modalities on AWS and Azure. Deploy ML solutions in containerized environments using Docker and Kubernetes. Integrate AI agents with APIs, cloud services, and databases. Apply MLOps, GitOps, and CI/CD practices to deployment, monitoring, and improvement of ML systems. Evaluate architectural tradeoffs and design service-based applications optimized for performance and scalability. Collaborate with cross-functional teams to deliver end-to-end solutions. Explore emerging AI/ML approaches, including LLMs, deep learning, and reinforcement learning. Communicate technical concepts clearly to both technical and non-technical stakeholders. Required Skills & Qualifications
3+ years of experience as an ML engineer building production-grade ML solutions, including work with LLMs, agents, or complex automation frameworks 3+ years of experience in data science or data research, training or deploying models across multiple data modalities 3+ years of experience in cloud environments (AWS and Azure) 2+ years of experience deploying and integrating production-grade ML models using Docker and Kubernetes Experience with LLMs, ML, DL, and RL Experience with AI agent frameworks such as LangChain, LangGraph, PydanticAI, or llamaindex Experience connecting agents to APIs, cloud platforms, or databases, and with MLOps, GitOps, and CI/CD tooling Experience evaluating architectural tradeoffs and designing robust service-based software for scalable use Secret clearance Bachelor’s degree Preferred Qualifications
Experience with TensorFlow, PyTorch, llama.cpp, and vLLM Experience with client engagements, project work, and business development Experience in deep learning, computer vision, NLP, or signal processing Experience deploying and managing data brokering solutions (e.g., Kafka, Red Panda, Confluent) Strong adaptability, communication, and interpersonal skills Master’s degree Job Details
Seniority level: Mid-Senior level Employment type: Full-time Job function: Engineering and Information Technology Industries: Staffing and Recruiting
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