Machine Learning Scientist- Digital Pathology and Medicine

Job details

About Us :

The people of Memorial Sloan Kettering Cancer Center (MSK) are united by a singular mission : ending cancer for life. Our specialized care teams provide personalized, compassionate, expert care to patients of all ages. Informed by basic research done at our Sloan Kettering Institute, scientists across MSK collaborate to conduct innovative translational and clinical research that is driving a revolution in our understanding of cancer as a disease and improving the ability to prevent, diagnose, and treat it. MSK is dedicated to training the next generation of scientists and clinicians, who go on to pursueour missionat MSK and around the globe.

Exciting Opportunity at MSK : Machine Learning Scientist- Digital Pathology and Medicine

Machine Learning Scientists at MSK combine advanced statistical methods, deep learning, and high-performance computing to extract insights from complex datasets-particularly in medical imaging and computational pathology. This role is ideal for independent, research-driven professionals who thrive on innovation, cross-functional collaboration, and advancing the boundaries of machine learning in healthcare.

Role Overview

Design and deploy deep learning and transformer-based models tailored for pathology applications.

Fine-tune large-scale AI and foundation models for clinical use cases.

Optimize self-supervised and few-shot learning approaches for digital pathology.

Translate research into production-ready AI tools used in healthcare environments.

Partner closely with clinicians and computational pathologists to ensure clinical integration.

Lead and contribute to high-impact publications in top AI and medical journals.

Mentor junior researchers, engineers, and postdoctoral fellows on technical direction and execution.

Support cross-functional initiatives to align AI development with healthcare delivery.

Drive the adoption of scalable AI solutions that meet clinical performance and reliability standards.

Key Qualifications

PhD or equivalent experience in Computer Science, Machine Learning, Computational Biology, or related field.

3+ years applying deep learning to real-world problems, ideally in medical imaging or healthcare AI.

Proficient in PyTorch and distributed / multinode training environments.

Proven experience with model deployment in high-stakes environments.

Knowledge of medical imaging, histopathology, and genomics preferred.

Core Skills

Strong programming expertise in Python, bash, and CUDA.

Experience with cloud platforms (AWS, GCP), HPC environments (e.g., SLURM), and infrastructure as code (Terraform).

Familiarity with containerization tools like Docker and Kubernetes.

Ability to balance academic rigor with practical deployment in healthcare systems.

Additional Information :

• Reporting to Physician Investigator, SKI

Schedule : 9 : 00 AM - 5 : 00 PM EST, Monday - Friday

Location : Hybrid; 99% remote with ability to come on site 1-2 times a year

Helpful Links :

Pay Range : $148,100.00 - $244,400.00 FSLA Status : Exempt

Closing :

At MSK, we believe in fair, competitive pay that reflects your job, experience, and skills.

MSK is an equal opportunity and affirmative action employer committed to diversity and inclusion in all aspects of recruiting and employment. All qualified individuals are encouraged to apply and will receive consideration without regard to race, color, gender, gender identity or expression, sexual orientation, national origin, age, religion, creed, disability, veteran status or any other factor which cannot lawfully be used as a basis for an employment decision.

Federal law requires employers to provide reasonable accommodation to qualified individuals with disabilities. Please tell us if you require a reasonable accommodation to apply for a job or to perform your job. Examples of reasonable accommodation include making a change to the application process or work procedures, providing documents in an alternate format, using a sign language interpreter, or using specialized equipment.