Agentic AI Machine Learning Engineer - Booz Allen Hamilton, Inc. - Fort Washington, MD
Booz Allen Hamilton, Inc.
Agentic AI Machine Learning Engineer
The Opportunity:
As an experienced machine learning engineer, you understand good software is more than just a good user experience. To compete in today's technical landscape, mission-oriented machine learning solutions must be architected, designed, and built to handle fast-moving data, to seamlessly scale with infrastructure based on system usage, and to expand based on evolving mission requirements. We're looking for an engineer like you to create artificial intelligence (AI) and machine learning (ML) enabled solutions that help solve our toughest challenges facing the Defense and Intelligence sectors.
On our team, you'll design, create, and implement complete AI systems that will transform client operations, increase data accessibility, and optimize AI and ML systems. You'll ensure that your team's solutions consider the broader ecosystem and operating environment as well as future functionality and enhancements. Additionally, you'll deepen your skill set in areas like software engineering, machine learning operations (MLOps), and software deployment and integration into a variety of different mission environments.
Ready to transform the Defense and Intelligence sectors with software systems to aid data accessibility and AI and ML operationalization?
Join us. The world can't wait.
You Have:
3+ years of experience as a ML engineer and building production-grade ML solutions, including work involving LLMs, agents, or complex automation frameworks3+ years of experience working within data science or data research in a professional or academic environment, and training or deploying models across multiple modalities of data3+ years of experience working in cloud environments, including AWS and Azure2+ years of experience deploying and integrating production-grade ML models using tools, such as Docker and KubernetesExperience with Large Language Models (LLM), Deep Learning (DL), and Reinforcement Learning (RL), and with tools