Senior ML Scientist: Medical Imaging & Survival (Equity)

Altis Labs; United States; On-site; USD 175,000 - 300,000; Full time

Benefits offered by this job

Equity participation

Health insurance

4 weeks vacation

Job summary

Altis Labs seeks a senior ML scientist to design and implement deep learning models for 3D medical imaging, focusing on survival analysis and time-to-event prediction. You will work on large-scale datasets (CT, PET, MRI) and contribute to cutting-edge IPRO technology that predicts patient outcomes to accelerate oncology trials.

The role requires a PhD or equivalent deep expertise in ML/CV with a strong research track record and experience with distributed training on cloud GPUs.

Qualifications

• 7+ years of ML experience, with substantial work in computer vision or medical imaging.
• PhD in ML, CV, statistics, or a related field; exceptional industry track record considered.
• Deep expertise in 3D vision—volumetric architectures (3D CNNs, Vision Transformers for 3D data).
• Strong foundation in survival analysis and time-to-event modeling (Cox models, deep survival models, competing risks).
• Experience training large models at scale; distributed training and memory optimization.

Responsibilities

• Design and implement deep learning architectures for 3D volumetric medical imaging (CT, PET, MRI).
• Develop survival models handling censored outcomes and competing risks.
• Optimize training pipelines for large-scale imaging datasets on cloud GPU infrastructure.
• Collaborate with ML team to establish best practices and advance state of the art.
• Contribute to research publications and present findings at conferences.

Skills

7+ years ML experience

3D vision expertise

Distributed training

PyTorch proficiency

Survival analysis knowledge

Research track record

Education

PhD in ML/CV/statistics or related field

Tools

PyTorch

Job description

Altis Labs seeks a senior ML scientist to design and implement deep learning models for 3D medical imaging, focusing on survival analysis and time-to-event prediction. You will work on large-scale datasets (CT, PET, MRI) and contribute to cutting-edge IPRO technology that predicts patient outcomes to accelerate oncology trials.

The role requires a PhD or equivalent deep expertise in ML/CV with a strong research track record and experience with distributed training on cloud GPUs.