Remote ML Engineer for Cancer Care & Multimodal AI

jobgether; New York (NY); Remote; USD 140,000 - 180,000; Full time

Benefits offered by this job

Remote work environment

401(k) with employer matching

Unlimited PTO

Equity as part of compensation

Job summary

jobgether is seeking a Machine Learning Engineer (Model Dev) based in the United States to develop ML solutions with impact on cancer care and clinical decision-making.

You will work across the full model-development lifecycle, from research to production deployment, focusing on multimodal pathology data, including whole-slide images and molecular information, collaborating with clinicians and engineers.

Qualifications

• At least 1 year of experience developing ML/deep-learning models using PyTorch or TensorFlow, including master's research.
• Familiarity with oncology biomarkers and cancer biology, endpoints and risk stratification.
• Experience with real-world datasets and appropriate metrics for evaluation.
• Strong Python skills and modern software practices (version control, testing, maintenance).
• Ability to analyze results, troubleshoot, and communicate conclusions effectively.
• Strong collaboration skills with cross-functional teams of engineers, clinicians and researchers.
• Experience with complex clinical datasets and ML in regulated healthcare environments is valuable.
• Familiarity with self-supervised learning, foundation models, or large-scale model development is a plus.
• Understanding dataset shift across sites, devices, scanners, or protocols is a plus.
• Research output through publications or conferences is valued, as is cloud-based ML development experience.

Responsibilities

• Develop and evaluate AI-based biomarkers from multimodal datasets to predict outcomes and molecular characteristics.
• Contribute to self-supervised foundation models and downstream ML systems (MIL, survival, segmentation, classification).
• Improve model robustness and reproducibility across scanners, institutions and protocols.
• Investigate interpretability techniques to increase clinician trust and model improvement opportunities.
• Build pipelines enabling efficient experimentation, validation, and deployment of ML models.
• Conduct rigorous evaluation, analyze results, troubleshoot behavior, and communicate findings clearly.
• Collaborate with ML scientists, engineers, clinicians, biostatisticians, product, regulatory, and QA teams.
• Support regulatory and quality documentation for AI model development and validation.
• Contribute to publications, conferences, and academia/industry collaborations.

Skills

Python

PyTorch

TensorFlow

Machine learning

Deep learning

Experimentation

Code testing

Version control

Tools

Git

Docker

Kubernetes

Job description

jobgether is seeking a Machine Learning Engineer (Model Dev) based in the United States to develop ML solutions with impact on cancer care and clinical decision-making.

You will work across the full model-development lifecycle, from research to production deployment, focusing on multimodal pathology data, including whole-slide images and molecular information, collaborating with clinicians and engineers.