Got rejected from ML Engineer role despite completing a tough take-home assignment, because of not knowing about specific tool(s) used for model versioning and retraining. Do you think it's fair or unfair?

I have 4.5 years of work experience in the data analytics/science domain, of which I spent:
- 2 years at one company as Data Analyst, where I was mostly building dashboards visualising predictions from sklearn models ("classical ML")
- 1.5 years at another company as a Data Scientist, where I was building PoC apps using deep learning algorithms, mostly computer vision, but a couple of NLP projects as well
- and the last 1 year at my current company as …

datascience engineer fair home role think tool versioning