Booz Allen

Defense and Intelligence sectors

AgenticAIMachineLearningEngineer

$99–99k Washington, District of Columbia, United States FULL TIME Remote Friendly
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Mid candidates.

The Brief

“Agentic AI Machine Learning Engineer at Booz Allen. Skills: Agentic AI, Machine Learning, LLMs, MLOps. Design AI systems. Create AI systems”

What You'll Achieve.

Solve toughest challenges; Transform client operations; Increase data accessibility; Optimize AI and ML systems; Aid data accessibility; AI and ML operationalization

Industry & Context.

Defense and Intelligence sectors
Problems you'll solve

Analytical skills; Problem-solving skills

Eligibility Requirements

Ability to obtain a Secret clearance, On camera during interviews, Identity verification process

What They're Looking For.

Must Have

3+ years of experience as a ML engineer, 3+ years of experience working within data science or data research, 3+ years of experience working in cloud environments, 2+ years of experience deploying and integrating production-grade ML models, Ability to obtain a Secret clearance, Bachelor’s degree

Nice to Have

Experience with programming, including ML frameworks, Experience with client engagements, Experience with project work in deep learning, computer vision, NLP, or signal processing, Experience deploying and managing data brokering solutions, Ability to adapt in a rapidly changing environment, Possession of excellent verbal and written communication skills, Possession of excellent interpersonal, analytical, problem-solving, and organizational skills, Secret clearance, Master's degree

What You'll Do.

Transform client operations

Increase data accessibility

Optimize AI and ML systems

Ensure solutions consider ecosystem

Deepen skill set in MLOps

Deepen skill set in software deployment

Deepen skill set in integration

How You'll Work.

Team & Collaboration

Work with product team; Collaborate with colleagues; Collaborate with customers

Communication Scope

Verbal communication skills; Written communication skills

Full Job Description

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 frameworks * 3+ 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 data * 3+ years of experience working in cloud environments, including AWS and Azure * 2+ years of experience deploying and integrating production-grade ML models using tools, such as Docker and Kubernetes * Experience with Large Language Models (LLM), Deep Learning (DL), and Reinforcement Learning (RL),

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