Vehicle Test Driver - Forest Lake, MN

Applus IDIADA•Hugo, MN
•$24 - $24•Onsite

About The Position

Applus+ IDIADA is seeking Driver Operators to join their team in Forest Lake, MN. The ideal candidate will be technically adept with general knowledge of the automotive industry. This role involves gathering data according to customer specifications across North America and documenting observations clearly using a Data Acquisition system. The position is project-based, expected to last 4-5 months with potential for consecutive projects. Applus+ IDIADA is a global partner to the automotive industry, offering design, engineering, testing, and homologation services. They are a TOP Employer certified company with a diverse team and international presence, focusing on innovation and adapting to the evolving automotive sector.

Requirements

  • High School diploma
  • 5 years of licensed driving experience
  • Must have current Driver's License and a clean driving record for a minimum of 3 years.
  • Must be physically able to support test preparation and execution in an outdoor environment.
  • Must be able to lift up to 50 pounds
  • Able to drive passenger vehicles up to 8 hours a day.
  • Meet all workplace health and safety requirements and practices.

Nice To Haves

  • Experience working with ADAS features highly preferred.

Responsibilities

  • Carry out various driving services on vehicles in line with customer specifications.
  • Drive and operate vehicles across a pre-defined routes through various terrain and weather conditions.
  • Perform predatory activities before shift, including but not limited to inspection of the vehicle before and after shift completion.
  • Manage data acquisition systems to ensure accurate data retrieval.
  • Drive vehicles in a safe manner and following traffic regulations.
  • Follow instructions provided by project manager.
  • Perform reporting activities daily and when required by the program manager.
  • Maintain all documentation with utmost confidentiality.
  • Support the acquisition of data and implement proper tagging techniques to document objects, obstacles, and anomalies found during data acquisition.
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