Vehicle Test Driver - Ann Arbor, MI

Applus IDIADA•Ann Arbor, MI
•Onsite

About The Position

Applus+ IDIADA is seeking Driver Operators to join their team in Ann Arbor, MI. The ideal candidate will be technically adept with general knowledge of the automotive industry and its products. This role involves gathering data according to customer specifications across North America and documenting observations through a Data Acquisition system. The project is 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. As a TOP Employer certified company, they have a large international team and network, supporting clients in developing safer, more efficient, and sustainable vehicles.

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 pre-defined routes through various terrain and weather conditions.
  • Perform preparatory activities before shift, including 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 the 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.
© 2026 Teal Labs, Inc
Privacy PolicyTerms of Service