Princeton On-Site AI & Software Instructor (12-Week)

Syllogic Learning LLC

Princeton (NJ)

In loco

USD 55.000 - 83.000

Tempo pieno

11 giorni fa

Una candidatura completa in un minuto

Curriculum e lettera di presentazione personalizzati, pronti da inviare.

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Descrizione del lavoro

Syllogic Learning LLC is seeking experienced software engineers and technical instructors to lead a 12-week, on-site training program in Princeton, NJ. You will teach hands-on labs in software engineering, cloud computing, and applied AI, guiding students through projects and evaluations.

The role emphasizes mentoring early-career engineers, delivering clear technical feedback, and maintaining production-oriented engineering skills among cohorts.

Competenze

  • Strong background in software engineering, AI/ML, or related technical disciplines.
  • Proficiency in Python and modern software development practices.
  • Experience with Generative AI, LLMs, RAG, and agentic AI workflows.
  • Familiarity with AWS and/or Azure, Docker, APIs, databases, and cloud deployment.

Mansioni

  • Deliver instructor-led technical training covering software engineering, cloud computing, and applied AI.
  • Guide students through hands-on labs, real-world engineering projects, and technical assessments.
  • Teach modern development practices, system architecture, deployment, and AI integration.
  • Mentor early-career engineers as they develop production-oriented engineering skills.
  • Evaluate student progress and provide actionable technical feedback.

Conoscenze

Python
Software Engineering
AI/ML
Cloud computing
Communication

Strumenti

Docker
APIs
AWS
Azure
Databases

Descrizione del lavoro

Syllogic Learning LLC is seeking experienced software engineers and technical instructors to lead a 12-week, on-site training program in Princeton, NJ. You will teach hands-on labs in software engineering, cloud computing, and applied AI, guiding students through projects and evaluations.

The role emphasizes mentoring early-career engineers, delivering clear technical feedback, and maintaining production-oriented engineering skills among cohorts.

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