Senior Deep Learning Engineer – Medical Computer Vision (Clinical AI)
Build Clinical AI That Saves Lives – From Day One
We are a newly established Australian MedTech company founded by a specialist clinician, focused on developing a clinical-grade Artificial Intelligence system for early melanoma detection using dermoscopy.
This is not a consumer app, marketing tool, or academic side project.
This is a regulated Software as a Medical Device (SaMD) being built for real-world clinical use.
We are now seeking a Senior Deep Learning Engineer to become our foundational technical leader and take ownership of the core computer vision system from architecture through to clinical deployment.
You will work directly with the medical founder, who provides expert, feature-level annotations — removing the single biggest weakness in most medical AI projects: poor-quality training data.
Why This Role Is Different
You are not joining a bloated tech team — you are building the AI engine from the ground up
Your work directly impacts real clinical diagnosis, not click-through rates
You will have true technical ownership, not a narrow Jira ticket role
You will be working with clean, expertly annotated medical data
You will play a central role in a TGA-regulated medical device project
Key Responsibilities
Design, implement, and optimise deep learning computer vision models for:
Dermoscopic feature segmentation (e.g., U-Net, Mask R-CNN)
Final lesion classification (benign vs malignant)
Build robust MLOps pipelines for training, validation, deployment, and monitoring
Lead all AI documentation required for:
TGA SaMD compliance
Model performance reporting
Risk analysis and data integrity
Implement Explainable AI (XAI) methods to support clinician trust
Work in close weekly collaboration with the clinical founder for validation and iteration
Essential Experience (Non-Negotiable)
2+ years of hands-on experience in Deep Learning / Machine Learning
Proven real-world experience with image segmentation (U-Net or similar is essential)
Academic project experience in image segmentation is acceptable as the minimum level of experience required
Strong proficiency in Python and PyTorch or TensorFlow
Experience deploying ML systems in cloud environments
Prior exposure to:
Medical imaging or
Regulated software environments (medical, safety-critical, ISO, or similar)
Highly Regarded
MSc or PhD in Computer Vision, AI, or a related discipline
Experience with multi-task learning
Strong understanding of clinical performance metrics (AUC, sensitivity, specificity)
Experience managing data bias and class imbalance in medical datasets
What We Offer
Highly competitive, above-market total remuneration based on experience
Performance-based bonuses
Relocation & settlement assistance within Australia for the right candidate
Hybrid flexibility once established
Direct access to clinical expertise and real-world validation
Long-term role stability in a founder-led MedTech venture
The opportunity to build technology that directly improves patient outcomes
Location – Why Mackay?
Affordable housing
Coastal living
Short commute times
Direct access to the Whitsundays
A growing healthcare and professional services sector
This role is ideal for someone who wants high-impact work without capital-city burnout.
?? Important – How to Apply
To be considered for this role, you must submit a tailored cover letter that clearly explains:
Why this role specifically interests you
Your most relevant experience in image segmentation and clinical AI
What excites you about building regulated medical software
Applications without a genuine, thoughtful cover letter will not be reviewed.
? Local Australian applicants only? No overseas sponsorship available
Be careful – don't provide your bank or credit card details when applying for jobs.
Don't transfer any money or complete suspicious online surveys.
If you see something suspicious, report this job ad.
#J-*****-Ljbffr