Question 1

What types of engineers does RunTime Recruitment place?

Accepted Answer

We specialise exclusively in deep tech hardware disciplines: embedded systems engineers, firmware engineers, FPGA engineers, DSP engineers, robotics engineers, control systems engineers, hardware engineers, and edge ML engineers. We do not place generalist software developers or IT professionals. Every candidate we work with has hands-on experience shipping real systems where failure has real consequences.

Question 2

Do you recruit in the United States as well as Australia?

Accepted Answer

Yes. We place engineers across both Australia and the United States. In Australia we work across defence, industrial automation, medtech, and consumer electronics. In the US we focus on IoT, robotics, defence, and semiconductor companies, particularly on the West Coast and in Texas. If you are a US company looking for embedded or firmware talent, we operate in your market.

Question 3

What industries do your candidates typically come from?

Accepted Answer

Our candidates come from defence and aerospace, industrial automation, medical devices, automotive and ADAS systems, consumer electronics, robotics, semiconductor design, and energy and power systems. These are industries where embedded systems failure is expensive and recovery is slow. Our candidates have shipped products in these environments and understand the constraints that come with them.

Question 4

How long does a typical placement take?

Accepted Answer

For most roles we present a shortlist of qualified candidates within two to three weeks. Time to placement from first brief to accepted offer typically runs four to six weeks depending on notice periods and interview scheduling. For senior or highly specialised roles such as FPGA architects or DSP engineers, allow six to eight weeks. We would rather take the time to find the right engineer than fill the seat quickly with the wrong one.

Question 5

What makes RunTime different from a generalist recruiter?

Accepted Answer

We only work in deep tech hardware. Our screening is grounded in how embedded systems actually fail, not keyword matching against a job description. We interrogate technical competence, we pressure-test candidates against your specific system constraints, and we will tell you when your expectations are unrealistic before you waste time interviewing the wrong people. Our 97% retention rate is the result of saying no more than yes. We are not trying to fill seats. We are trying to reduce your hiring risk.

Tag: Machine Learning