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Data/AI · Work role code 623

AI/ML Specialist

Designs, develops, and modifies AI applications, tools, and/or other solutions to enable successful accomplishment of mission objectives.

From DoD DCWF Tool v5.3 (2026-09-25)

Tasks

From DoD DCWF Tool v5.3 (2026-09-25), in the tool's order, with the DCWF KSAT id

Free · DoD DCWF Tool v5.3 (2026-09-25)
  • 477Correct errors by making appropriate changes and rechecking the program to ensure desired results are produced.Core
  • 506Design, develop, and modify software systems, using scientific analysis and mathematical models to predict and measure outcome and consequences of design.Core
  • 543Develop secure code and error handling.Core
  • 764Perform secure programming and identify potential flaws in codes to mitigate vulnerabilities.Core
  • 1000BEnsure that AI design and development activities are properly documented and updated.Core
  • 5120Conduct hypothesis testing using statistical processes.Core
  • 5847Assess and address the limitations of methods to deliver machine learning models.Core
  • 5854Collaborate with appropriate personnel to address Personal Health Information (PHI), Personally Identifiable Information (PII), and other data privacy and data reusability concerns for AI solutions.Additional
  • 5858Conduct AI risk assessments to ensure models and/or other solutions are performing as designed.Core
  • 5859Consider energy implications (graphical processing unit, tensor processing unit, etc.) when designing AI solutions.Additional
  • 5870Design and develop continuous integration/continuous delivery (CI/CD) in a containerized or other reproducible computing environment to support the machine learning life cycle.Additional
  • 5871Design and develop machine learning models to achieve organizational objectives.Core
  • 5872Design, develop, and implement AI tools and techniques to achieve organizational objectives.Core
  • 5873Determine methods and metrics for quantitative and qualitative measurement of AI risks so that sensitivity, specificity, likelihood, confidence levels, and other metrics are identified, documented, and applied.Core
  • 5889Identify and submit exemplary AI use cases, best practices, failure modes, and risk mitigation strategies, including after-action reports.Additional
  • 5893Implement Responsible AI best practices and standards within AI solutions according to the DoD AI Ethical Principles, Responsible AI Guidelines, and/or any other pertinent laws.Additional
  • 5896Maintain current knowledge of advancements in DoD AI Ethical Principles and Responsible AI.Core
  • 5915Research the latest machine learning and AI tools, techniques, and best practices.Core
  • 5925Use knowledge of business processes to create or recommend AI solutions.Additional
  • 5926Use models and other methods for evaluating AI performance.Core
  • 5927Write and document reproducible code.Core

Knowledge

From DoD DCWF Tool v5.3 (2026-09-25), in the tool's order, with the DCWF KSAT id

Free · DoD DCWF Tool v5.3 (2026-09-25)
  • 21Knowledge of computer algorithms.Core
  • 22* Knowledge of computer networking concepts and protocols, and network security methodologies.Core
  • 75AKnowledge of mathematics, including logarithms, trigonometry, linear algebra, calculus, statistics, and operational analysis.Core
  • 102Knowledge of programming language structures and logic.Core
  • 108* Knowledge of risk management processes (e.g., methods for assessing and mitigating risk).Core
  • 942Knowledge of the organization's core business/mission processes.Additional
  • 1157* Knowledge of national and international laws, regulations, policies, and ethics as they relate to cybersecurity.Core
  • 1158* Knowledge of cybersecurity principles.Core
  • 1159* Knowledge of cyber threats and vulnerabilities.Core
  • 6290Knowledge of how to leverage government research and development centers, think tanks, academic research, and industry systems.Additional
  • 6311Knowledge of machine learning theory and principles.Core
  • 6900* Knowledge of specific operational impacts of cybersecurity lapses.Core
  • 6935* Knowledge of cloud computing service models Software as Service (SaaS), Infrastructure as a Service (IaaS), and Platform as a Service (PaaS).Core
  • 6938* Knowledge of cloud computing deployment models in private, public, and hybrid environment and the difference between on-premises and off-premises environments.Core
  • 7003Knowledge of AI security risks, threats, and vulnerabilities and potential risk mitigation solutions.Additional
  • 7009Knowledge of coding and scripting in languages that support AI development and use.Core
  • 7011Knowledge of current AI and machine learning systems design and performance analysis models, algorithms, and tools.Core
  • 7020Knowledge of DoD AI Ethical Principles (e.g., responsible, equitable, traceable, reliable, and governable).Core
  • 7021Knowledge of emerging trends and future use cases of AI.Additional
  • 7022Knowledge of how AI adoption can assist developers with service-oriented design.Additional
  • 7024Knowledge of how AI is developed and operated.Core
  • 7025Knowledge of how AI solutions integrate with cloud or other IT infrastructure.Additional
  • 7026Knowledge of how commercial and federal solutions solve Defense-related data environment and platform challenges.Additional
  • 7028Knowledge of how to automate development, testing, security, and deployment of AI/machine learning-enabled software.Core
  • 7029Knowledge of how to collect, store, and monitor data.Core
  • 7031Knowledge of how to structure and display data.Core
  • 7032Knowledge of how to use data to tell a story.Core
  • 7036Knowledge of laws, regulations, and policies related to AI, data security/privacy, and use of publicly procured data for government.Additional
  • 7037Knowledge of machine learning operations (MLOps) processes and best practices.Core
  • 7038Knowledge of metrics to evaluate the effectiveness of machine learning models.Core
  • 7040Knowledge of Personal Health Information (PHI), Personally Identifiable Information (PII), and other data privacy and data reusability considerations for AI solutions.Additional
  • 7041Knowledge of remedies against unintended bias in AI solutions.Additional
  • 7044Knowledge of testing, evaluation, validation, and verification (T&E, V&V) tools and procedures to ensure systems are working as intended.Additional
  • 7045Knowledge of the AI lifecycle.Core
  • 7046Knowledge of the basic requirements for the successful delivery of AI solutions.Core
  • 7048Knowledge of the benefits and limitations of AI capabilities.Core
  • 7049Knowledge of the latest machine learning and AI tools, techniques, and best practices.Core
  • 7050Knowledge of the nature and function of technology platforms and tools used to create and employ AI.Core
  • 7051Knowledge of the possible impacts of machine learning blind spots and edge cases.Core
  • 7111* Knowledge of Zero Trust Security Model Principles.Core

Skills

From DoD DCWF Tool v5.3 (2026-09-25), in the tool's order, with the DCWF KSAT id

Free · DoD DCWF Tool v5.3 (2026-09-25)
  • 166Skill in conducting queries and developing algorithms to analyze data structures.Core
  • 6760Skill in writing scripts using R, Python, PIG, HIVE, SQL, etc.Core
  • 7055Skill in analyzing the output from machine learning models.Core
  • 7057Skill in building and deploying machine learning models.Core
  • 7059Skill in creating machine learning models.Core
  • 7065Skill in explaining AI concepts and terminology.Core
  • 7067Skill in identifying low-probability, high-impact risks in machine learning training data sets.Core
  • 7069Skill in identifying risk over the lifespan of an AI solution.Additional
  • 7071Skill in labeling data to make it more discoverable and understandable.Additional
  • 7075Skill in testing and evaluating machine learning algorithms and/or AI solutions.Core

Abilities

From DoD DCWF Tool v5.3 (2026-09-25), in the tool's order, with the DCWF KSAT id

Free · DoD DCWF Tool v5.3 (2026-09-25)
  • 6060Ability to collect, verify, and validate test data.Core

Workforce Automation analysis, not part of the source

O*NET jobs

WFA · Part of the paid plan when accounts open

Jobs the ETO-CSET NICE/O*NET crosswalk (2024) maps to this role’s NICE equivalents, with the share of each job’s detailed work activities (DWAs) that has a mapped AI skill.

No O*NET jobs reach this role.

    Equivalents

    NICE work roles

    From DoD DCWF Tool v5.3 (2026-09-25), linked from published ids only, never from titles

    Free · DoD DCWF Tool v5.3 (2026-09-25)

    No published NICE equivalent.

    O*NET jobs it reaches

    Through its NICE equivalents, by the ETO-CSET NICE/O*NET crosswalk (2024); jobs from O*NET 30.3

    Free · O*NET 30.3

    No O*NET job reaches this role.