Entry Level Engineer - Austin

Vertech10 months ago
Austin, TX, United States
Hybrid
Full-time
Beginner Level (< 1 year)

Job Description

Position Overview

Do you want the opportunity to develop control systems for some of the nation’s greatest companies? A chance to work on world-changing projects that enable clean and affordable electricity and quick access to clean water? If making the world a better place through controls and engineering sounds exciting, join us as a Control Freak. At Vertech, we develop world-class industrial automation solutions for top US companies while fostering a culture of excellence, fun, and growth.

Key Responsibilities

  • Learn the full spectrum of a project from defining, designing, developing, demonstrating, to delivering PLC/HMI based control systems.
  • Write structured, well-documented, and bug-free PLC code.
  • Design intuitive, easy-to-navigate, and aesthetically pleasing HMI interfaces.
  • Work on various projects developing PLC code and HMI screens within the first year.
  • Engage in high-level programming using languages such as .NET, Java, Python, C, and C++.
  • Gain familiarity with SCADA and MES packages along with the associated terminology.
  • Collaborate in project teams ranging from 2-10 people with diverse technology backgrounds.

Required Qualifications

  • BS in electrical, mechanical, chemical, or a related engineering field.
  • Ability to learn quickly.
  • Availability to travel up to 20%.

Benefits & Perks

  • Flexible work schedule with work from home options.
  • Weekly communication from management during our famous Friday morning meeting.
  • Competitive Compensation including a bonus plan.
  • Benefits, including a 401k, kick in within 4 weeks.
  • A really rad Christmas Party each year.
  • Supportive management, great culture, PTO, and pathways for growth.

Required Skills

Industrial Automation
Team Collaboration
SCADA Systems
Project Development
HMI Design
High-Level Language Programming (.NET, Java, Python, C, C++)
PLC Programming
Quick Learning