Case Study: Software Development

Programmed for Success: The Data is in the Details

After further diving into the details… our Client was compelled to conduct an interview.

  • Position: Embedded Sortware Engineer: Deep Learning Systems
  • Client: Dynamic R&D company managing cutting edge projects using AI and Deep/Machine Learning systems
  • Issue: Our Client is a very small R&D company typically working on technical projects for the U.S. Government. The projects are classified, specifics cannot be discussed, and require highly technical engineering skill sets. Due to these aspects, the Client saw little success with previous recruiters and was wary to engage another recruiting agency.

  • Solution: Career Transitions was tasked with finding a Sr. Embedded Software Engineer with Deep Learning Systems experience for our Client’s growing Artificial Intelligence team. Minimally the candidate needed a Master’s in Computer Science/Engineering, but a Ph.D. was preferred. In addition, the candidate needed experience with image processing, video-based behavior analysis, and current programming skills with C, C++, and C#.

    We sourced 35 candidates meeting the criteria. Six qualified finalists were presented to our Client. Ultimately, they were not quite the right fit, and were passed on for the role.

    The 7th and final candidate we presented came from a large company. However, our Client was concerned the candidate would not be compatible in their smaller startup environment. After further diving into the details and explaining this individual had worked on a small custom development team which focused on Deep/Machine Learning systems – within the large company – they were compelled to conduct an interview.

    At last, it was a match. Our Client hired the candidate, relocated them from MI to TX, and the Engineer started the new role – all within 60 days of the initial recruiting intake call.

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