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About the Role
We are seeking a talented individual to design and implement deep learning architectures for 3D volumetric medical imaging and develop survival models. This role offers access to unusually rich data, novel methodology development, and the opportunity to work on multi-cancer generalization.
Responsibilities
- Design and implement deep learning architectures for 3D volumetric medical imaging (CT, PET, MRI)
- Develop survival models that handle censored outcomes, competing risks, and the statistical nuances of time-to-event prediction
- Optimize training pipelines to efficiently process large-scale imaging datasets on cloud GPU infrastructure
- Collaborate with our ML team to establish best practices and push the state of the art
- Contribute to research publications and present findings at conferences
Requirements
- 7+ years of experience in machine learning, with substantial work in computer vision or medical imaging
- Deep expertise in 3D vision—experience with volumetric architectures (3D CNNs, Vision Transformers for 3D data, etc.)
- Strong foundation in survival analysis and time-to-event modeling (Cox models, deep survival models, competing risks)
- Proven ability to train large models efficiently at scale—you understand distributed training, memory optimization, and what it takes to iterate quickly on big data
- Proficiency with PyTorch and modern ML infrastructure
- Track record of impactful research (publications, deployed systems, or equivalent demonstrations of technical depth)
Skills
- Machine learning
- Computer vision
- Medical imaging
- 3D vision
- Volumetric architectures
- 3D CNNs
- Vision Transformers for 3D data
- Survival analysis
- Time-to-event modeling
- Cox models
- Deep survival models
- Competing risks
- Distributed training
- Memory optimization
- PyTorch
- ML infrastructure
- Medical imaging foundation models
- Self-supervised learning
- Uncertainty quantification
- Calibrated predictions
- Conformal prediction
- Bayesian deep learning
- MLOps
- CI/CD for ML
- Model monitoring
- Oncology
- Radiology
- Regulated healthcare environments
Location
- Toronto
Work Type
- Full-time
Experience Level
- 7+ years of experience in machine learning
Education Level
- PhD in machine learning, computer vision, statistics, or a related field preferred; exceptional industry track record considered
Benefits
- Competitive pay and generous equity participation
- Coverage for medical, vision, and dental insurance
- 4 weeks of vacation per year
About the Company
- Altis Labs is a computational imaging company focused on improving how oncology trials measure treatment benefit.
- Our core technology is IPRO, an AI model that generates patient-level outcome predictions directly from routine medical imaging data.
- Our global biopharma customers use IPRO to predict efficacy, navigate billion-dollar development decisions with confidence, and move their most promising therapies through Phase I–III trials faster.
- IPRO is trained on the industry’s largest real-world imaging, clinical, and outcomes database, containing over 210 million longitudinal images and more than one million patient-years of linked outcomes.
- Our multidisciplinary team of AI scientists, clinicians, and business operators is on a mission to get the most effective treatments to patients sooner.
- We collaborate closely with academic medical centers and co-publish our results at top-tier medical conferences.
- Altis is headquartered in Toronto, serves 6 of the top 20 global biopharmaceutical companies, and is backed by leading life sciences and technology investors.