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Auburn University

Principal Research Scientist/Engineer 1/2/3/4/5/VI/VII

Applied Machine LearningUpdated on Nov 11
Full-timeHuntsville, AL, USANo salary listedIn-person

About the Job

Requirements

  • A PhD from an accredited institution in Engineering, Science, Management Information Science, or a related technical field is required; relevant experience may substitute toward the PhD requirement at a rate of two years of experience per year of required education.
  • Level I requires no experience; Level II requires 2 years of professional experience; Level III requires 4 years; Level IV requires 6 years; Level V requires 8 years; Level VI requires 10 years; and Level VII requires 12 years, in engineering and research practices and principles or science-based programs.
  • Knowledge of research principles, laboratory techniques, and safety procedures.
  • Competence in all conventional aspects of the assigned subject matter or functional areas.

Responsibilities

  • Set and maintain the technical roadmap for AI, data, and software capabilities across Edge Lab programs.
  • Lead multidisciplinary research and development projects from problem framing and experimental design through prototype, validation, deployment, and transition.
  • Design and review software architectures, application programming interfaces, data pipelines, model-serving patterns, user-facing applications, and integration approaches.
  • Establish engineering practices for source control, automated testing, continuous integration and continuous delivery, secure software development, documentation, code review, and release management.
  • Develop responsible artificial intelligence and machine-learning operations practices covering data governance, evaluation, model risk, monitoring, reproducibility, privacy, and lifecycle management.
  • Provide hands-on technical contributions using appropriate programming languages, cloud and on-premises platforms, artificial intelligence frameworks, and data technologies.
  • Guide the selection and integration of foundation models, machine-learning methods, retrieval systems, agents, and other artificial intelligence techniques based on mission need and evidence.
  • Partner with the Technology Architect and Senior Cybersecurity Analyst to ensure solutions are resilient, secure, observable, and deployable in customer environments.
  • Mentor engineers, researchers, students, and technical staff; assign work, review technical quality, and expand team capacity.
  • Develop technical concepts, proposals, budgets, schedules, demonstrations, reports, publications, and executive and customer briefings.
  • Lead knowledge transfer from software and artificial intelligence consultants and assume ownership of reusable code, platforms, and technical decisions.

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