Staff Mechanical Engineer - AI-Driven Nuclear Systems

thenuclearcompany; Columbia (SC); On-site; USD 120,000 - 160,000; Full time

Benefits offered by this job

Competitive compensation

401k with company match

Medical, dental, vision plans

Job summary

The Nuclear Company is leading AI-enabled innovation in the nuclear and energy space. The Staff Mechanical Engineer will lead design, analysis, and maintenance of complex mechanical systems for operating or new nuclear plants, using AMSE/ANSI codes and supporting cross-disciplinary teams.

We value safety, rigorous engineering, and continuous learning, with AI-driven tools and digital twin concepts to accelerate performance and reliability across plant systems.

Qualifications

• ABET-accredited BS in Mechanical Engineering is required.
• Strong analytical and problem-solving abilities.
• Excellent communication and interpersonal skills.

Responsibilities

• Design and analysis of mechanical components and systems.
• Prepare engineering calculations, drawings and specifications.
• Prepare or review engineering modification packages.
• Provide technical guidance to junior engineering staff.
• Diagnose mechanical equipment failures and implement corrective actions.
• Conduct calculations to ensure structural integrity and performance of systems.
• Review vendor documentation and technical specs.
• Participate in design reviews and technical meetings.
• Interface with civil/structural, electrical and I&C engineers.
• Support QA/QC programs and prepare technical reports.

Skills

Analytical thinking

Problem-solving

Team collaboration

Education

ABET-accredited BS in Mechanical Engineering

Tools

AutoCAD

SolidWorks

ANSYS

Job description

The Nuclear Company is leading AI-enabled innovation in the nuclear and energy space. The Staff Mechanical Engineer will lead design, analysis, and maintenance of complex mechanical systems for operating or new nuclear plants, using AMSE/ANSI codes and supporting cross-disciplinary teams.

We value safety, rigorous engineering, and continuous learning, with AI-driven tools and digital twin concepts to accelerate performance and reliability across plant systems.