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Senior AI/ML Developer
M9 Solutions. Design and deploy scalable AI/ML models supporting the client mission .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in designing and deploying scalable AI/ML models while ensuring compliance with federal cybersecurity and data governance standards. Proficient in integrating AI solutions into secure environments and managing the model lifecycle with a focus on validation and bias mitigation.
Highest-signal resume keywords
AI/ML Solution DevelopmentMLOps PracticesPython, R, Java ProficiencyAWS, Azure, Google Cloud ExperiencePublic Trust Security Clearance
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
AI/ML Model DesignPredictive Analytics DevelopmentData Engineering OversightModel Lifecycle ManagementTensorFlow, PyTorch ExpertiseRetrieval-Augmented Generation (RAG)Agile DevelopmentJIRA ProficiencyAI Governance PracticesZero Trust Architecture Knowledge
Soft Skills
Strong Communication SkillsMultitasking AbilityTechnical Assistance Experience
Tools & Technologies
AWS SageMakerAWS BedrockAzure AI FoundryGoogle Vertex AISalesforce Solutions
Certifications & Qualifications
Bachelor's Degree or HigherPublic Trust Security Clearance
Industry Keywords
Cybersecurity ComplianceData Governance StandardsFederal Risk Management FrameworkIncident Response DocumentationU.S. Federal Agencies Experience
Tech Stack
Tools & technologiesAWSAzureCloudCyber SecurityJavaPythonPyTorchTensorflow
About the role
Key responsibilities & impact- Design and deploy scalable AI/ML models supporting the client mission
- Develop predictive analytics, automation frameworks, and intelligent decision-support systems
- Integrate AI solutions into secure enterprise and tactical environments
- Ensure compliance with federal cybersecurity and data governance standards
- Provide oversight of data engineering pipelines and model lifecycle management (MLOps)
- Develop and maintain model validation, explainability, and bias mitigation practices
- Advise program leadership and stakeholders on emerging AI technologies and mission applications
- Support transition of experimental or prototype AI capabilities into operational production systems
- Integrate security, ethical, and data governance requirements into AI development workflows in alignment with federal Risk Management Framework expectations
- Assess AI security threats and produce ATO, configuration management, and incident response documentation
- Coordinate with ISSOs, business owners, and stakeholders to implement secure AI solutions
- Participate in audits, interviews, and governance reviews
Requirements
What you’ll need- Public Trust security clearance
- Bachelor's degree or higher
- 10+ years of progressive experience in AI/ML, data science, software engineering, or related advanced analytics disciplines, including hands-on experience with modern AI technologies
- 5+ years of hands-on experience designing, developing, and deploying AI/ML solutions in production environments, including modern AI technologies and MLOps practices
- Proficiency in Python, R, and/or Java
- Deep understanding of TensorFlow or PyTorch, preferably implemented within AWS SageMaker
- Experience integrating AI/ML capabilities into secure enterprise environments and adhering to cybersecurity, data governance, and compliance requirements
- Experience developing AI products or functional prototypes using Retrieval-Augmented Generation (RAG) and agentic AI technologies
- Experience with AWS, Azure, or Google Cloud and AI services such as AWS Bedrock, Azure AI Foundry, or Google Vertex AI
- Experience implementing AI solutions in secure, restricted, or regulated environments
- Hands-on experience with agile development and JIRA
- Strong communication skills with the ability to present ideas to various levels and skillsets, internally and externally
- Technical assistance and end-user troubleshooting experience for bug fixes, enhancements, and how-to assistance
- Ability to multitask between multiple projects and business and technical stakeholders
- Experience supporting enterprise-scale Salesforce solutions; Agentforce implementation experience highly preferred
- Familiarity with AI governance practices and modernization initiatives
- Experience working with or supporting U.S. federal agencies
- Experience deploying AI/ML solutions in AWS GovCloud or Azure Government
- Knowledge of Zero Trust architectures and integrating cybersecurity principles into AI/ML systems
Benefits
Comp & perks- Competitive compensation package
- M9 Benefits (specific benefits linked at https://m9solutions.com/why-join-m9/#our-benefits)