We recruit AI and data engineers in Australia, senior through to principal. Both founders are engineers, so we run the technical conversation ourselves and tell you what we actually think of each person.
Illustrative of a typical shortlist, not live candidate data.
Precision and recall are the two measures used to judge a machine learning model. They pull against each other, and a model that is good at one and bad at the other is not much use. Recruitment has the same two failure modes, and it is easy to fix one by giving up on the other.
Of the people we send you, how many are genuinely worth interviewing. A long shortlist is easy to produce and expensive to read. Ours is three to five people, each with a written assessment of what they have built and where they would need support.
precision = TP / (TP + FP)
Of the people who could do the job, how many we actually reached. The engineers worth hiring are usually employed and not applying to anything. Finding them takes a network and direct approach rather than a job ad, and that is most of what the work is.
recall = TP / (TP + FN)
Three roles that look the same on a CV and are different jobs in practice. We hire against the work each one actually does.
Sets up the stack, connects your data, and gets AI running against a real workflow inside your business. Sits close to the people who will use it.
Takes a model from prototype to production and keeps it working as the data and the traffic change. Serving, evaluation, monitoring, retraining.
Builds the pipelines and the platform your reporting and your models both run on. The unglamorous layer everything else depends on.
We also recruit machine learning engineers, analytics engineers and data platform engineers. If the role sits somewhere between these, that is normal and worth a conversation.
Thirty minutes on what the system has to do, what it has to reach, and who owns it afterwards. We tell you whether the brief as written is fillable.
Three to five people, each with notes on what they have built, how they were assessed, and where they would need support.
We run the process, do the technical reference checks, and stay involved through notice periods to the start date.
Both founders are engineers. One is a Chief Data & AI Officer with a research background in deep learning, and a career through enterprise transformation and GM roles in AI. The other has spent twelve years building production data platforms.
Between them they have done this work and hired for it, so they assess candidates directly instead of matching keywords on a CV.
Many of the people worth hiring for these roles are already employed and are not applying for anything. Reaching them takes a network rather than a job ad.
That is most of what we do, and it is why our shortlists tend not to overlap with the ones you will get elsewhere.
A 30-minute call is enough for us to tell you whether the role is fillable and who is available. If we cannot help we will say so.
Tell us about a role