Booz Allen

ArtificialIntelligenceandMachineLearningEngineer,Lead

$129–129k Camp Lejeune, North Carolina, United States FULL TIME Remote Friendly
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Lead candidates.

The Brief

“Artificial Intelligence and Machine Learning Engineer, Lead at Booz Allen. Skills: AI, Machine Learning, MLOps, Data orchestration. Lead AI microservices deployment. Operationalize scalable AI microservices”

What You'll Achieve.

Drive operational readiness; Drive tactical decision making; Enhance situational awareness; Optimize mission execution

Industry & Context.

Problems you'll solve

Unlock secrets held by data set; Fascinated by possibilities

Eligibility Requirements

Secret clearance, TS/SCI clearance

What They're Looking For.

Must Have

Secret clearance, Bachelor's degree in a Data Science or Mathematical field

Nice to Have

Experience building ETL/ELT pipelines from external data lakes and systems such as the War Data Platform (WDP), Palantir Maven Smart System (MSS), Cloud Platforms such as Azure, AWS, or GCP, and SharePoint, Experience with other DoW enterprise data platforms such as Advana or MSS, Experience with Lean-Agile methodologies and frameworks such as Scrum or Scaled Agile Framework (SAFe), Experience managing project workflows and documentation across Jira and Confluence for alignment to concurrent initiatives, Knowledge of USMC operational planning, intelligence cycles, or logistics processes, TS/SCI clearance, Master's degree in an Artificial Intelligence or Machine Learning related field

What You'll Do.

Lead AI microservices deployment

Operationalize scalable AI microservices

Develop production-grade APIs

Use containerization and orchestration

Deliver automated model serving

Implement CI/CD pipelines

Design data orchestration

Deploy scalable ETL/ELT pipelines

Build production microservices

Apply deep technical knowledge

Develop and deploy solutions

Inform client's technical strategy

Design complex systems

Implement complex systems

How You'll Work.

Team & Collaboration

Work directly with client; Work with stakeholders; Cross-functional efforts; Support cross-functional collaboration; Align with stakeholders

Communication Scope

Communicate complex technical concepts

Process & Methodology

Manage project workflows, Manage documentation

Full Job Description

Artificial Intelligence and Machine Learning Engineer, Lead **The Opportunity:** Are you excited at the prospect of unlocking the secrets held by a data set? Are you fascinated by the possibilities presented by the IoT, machine learning, and artificial intelligence advances? As an MLOps Engineer, you have a passion for leveraging Department of War (DoW) data to drive operational readiness and tactical decision making. You excel at designing, building, and operationalizing scalable solutions in secure enterprise environments integrating datasets from disparate systems. As a member on our team, you’ll work directly with the client and stakeholders to architect data-driven solutions that enhance situational awareness and optimize mission execution. You will apply your deep technical knowledge in data orchestration and the development and deployment of solutions to production environments to inform the client’s technical strategy for designing and implementing complex systems. Join us. The world can't wait. **You Have:** * Experience leading the deployment and operationalization of scalable AI microservices, including the development of production-grade APIs using containerization and orchestration, to deliver automated model serving and CI/CD pipelines for production application * Experience with data orchestration and containerization tools, such as Docker, Kubernetes, NIFI, or Airflow, to design, deploy and maintain scalable ETL/ELT pipelines, data flows, and production microservices to cloud environments * Experience leading or participating in cross-functional efforts to complete ATO accreditation for release of products in production environment * Experience implementing MLOps best practices, including model monitoring, drift detection, and automated retraining workflows, while maintaining strict compliance in regulated cloud environments * Experience in multiple programming and scripting languages, such as Python, Java, Bash, Shell, SQL, HCL, YAML, JavaScript, or

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