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Specialisms - AI Engineering - Healthtech
Australian healthtech runs some of the most advanced applied AI in the country: diagnostic imaging at Harrison.AI and Annalise.AI, clinical NLP, and medical decision support. Re:Sourced recruits ML engineers who understand that healthcare AI ships under TGA software-as-medical-device rules, clinical safety frameworks and privacy constraints that reshape the engineering itself.
The profile
Computer vision for diagnostic imaging dominates the senior end of the market: radiology, pathology and ophthalmology models that operate as regulated medical devices. The second cluster is clinical NLP - extracting structure from notes, discharge summaries and referral letters. The third is operational ML inside telehealth platforms: triage, scheduling and demand prediction.
The scarce capability is regulatory fluency. Engineers who have taken a model through TGA SaMD classification or FDA clearance understand validation datasets, clinical evidence requirements and post-market monitoring. That experience commands a premium and shortens a healthtech employer time-to-market materially.
Where they come from
Harrison.AI and Annalise.AI alumni form the densest single pool in Sydney. Melbourne adds A2 Optics and the university medical-AI labs (Monash, Melbourne) whose research engineers increasingly move into industry. The cross-over pattern from general computer vision into medical imaging works well when the candidate has shipped production CV; pure research profiles take longer to land.
Senior healthtech ML engineers price within the standard AI band (AUD 180-220k base in Sydney), with regulatory-experienced candidates at the top. Base only, 25th-75th percentile of accepted offers.
Submit a brief
30 minute working session. No fee until placement. Replacement inside 90 days.