Booz Allen
ArtificialIntelligenceandMachineLearningEngineer,Lead
Neural analysis suggests this role is
optimal for Lead candidates.
“Artificial Intelligence and Machine Learning Engineer, Lead at Booz Allen. Skills: AI, Machine Learning, MLOps, Data Engineering. Design scalable solutions. Build scalable solutions”
What You'll Achieve.
Drive operational readiness; Drive tactical decision making; Enhance situational awareness; Optimize mission execution
Industry & Context.
Unlock data secrets; Leverage data
Secret clearance, On camera during interviews, Identity verification process
What They're Looking For.
Must Have
Experience leading deployment and operationalization of scalable AI microservices, Experience with data orchestration and containerization tools, Experience leading or participating in cross-functional efforts to complete ATO accreditation, Experience implementing MLOps best practices, Experience in multiple programming and scripting languages, Experience in communicating complex technical concepts, Experience creating clear and comprehensive architecture diagrams, Knowledge of NIST SP 800-53 controls, Secret clearance required, Bachelor's degree in Data Science or Mathematical field
Nice to Have
Experience building ETL/ELT pipelines from external data lakes, Experience with other DoW enterprise data platforms, Experience with Lean-Agile methodologies and frameworks, Experience managing project workflows and documentation, Knowledge of USMC operational planning, intelligence cycles, or logistics processes, TS/SCI clearance, Master's degree in AI or ML related field
What You'll Do.
Design scalable solutions
Build scalable solutions
Operationalize scalable solutions
Integrate datasets from disparate systems
Architect data-driven solutions
Enhance situational awareness
Optimize mission execution
Develop production-grade APIs
Deliver automated model serving
Maintain CI/CD pipelines
Design ETL/ELT pipelines
Deploy ETL/ELT pipelines
Maintain ETL/ELT pipelines
Design production microservices
Deploy production microservices
Maintain production microservices
Complete ATO accreditation
Implement MLOps best practices
Retrain models automatically
Support full-stack development efforts
Communicate technical concepts
Create architecture diagrams
Create data flow diagrams
Create system design documentation
How You'll Work.
Team & Collaboration
Cross-functional efforts; Stakeholder alignment; Cross-functional collaboration
Communication Scope
Technical concepts; Architecture diagrams; Data flow diagrams; System design documentation
Process & Methodology
Lean-Agile methodologies, Scrum, SAFe
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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