Adaptive Tactics [AT] Careers
AI Job Categories
AI models its staffing seniority grade levels to the engineering levels established by the Institute of Electrical and Electronics Engineers (IEEE), as follows:
A data scientist (DS) serves as the central integrator of human-machine intelligence (HMI) capabilities. Using domain expertise, a DS will sufficiently model and characterize data using statistical and signal processing methods to inform ML algorithm selection and configuration using a mature data architecture that seamlessly integrates into a software architecture for product implementation.
A software engineer (SE) serves as the key implementer of machine intelligence (MI) algorithms. A successful SE will apply their hard science background to suggest refinements to features and algorithm selection and configuration collaboratively with data science and data engineer team members. This is in contrast to a software programmer (SP) who only has a computer science degree.
A data engineer (DE) serves to aggregate and normalize data from many sources of observations that are then processed to generate activity features that summarize the key attributes of the data collected using Key DE skills. An effective DE team member will closely coordinate with a data scientist (DS) on each project to scope, design, and implement project-based work. Generated feature and selected raw data will be saved to a persistent data store to enable historical analysis and higher context feature generation to support machine intelligence (MI) applications.
A product architect (PA) serves as an architect of [AI] human machine intelligence (HMI) capabilities. Closely coordinating with data scientist (DS) and software engineering (SE) team members, a PA will solicit design concepts and work to elaborate their implementation details into written form to maintain architectural integrity to satisfy system requirements (SR) from the product management (PM) team.