Senior Research Engineer

NYU Grossman School of Medicine; New York (NY); On-site; USD 101,493 - 132,088; Full time

Job summary

NYU Grossman School of Medicine is launching a Senior Machine Learning Research Engineer role within CODA to develop multimodal ML systems for musculoskeletal care. You will architect data pipelines for radiographic imaging, clinical data, and other modalities, and work with a multidisciplinary team to translate clinical goals into robust ML solutions.

You will build end-to-end pipelines, establish engineering standards, and contribute to research and publications while collaborating with

Qualifications

• 3+ years of ML experience in industry or equivalent (e.g., dissertation work).
• Strong programming in Python/SQL with large relational datasets.
• Expertise in PyTorch and TensorFlow; Docker familiarity.
• Proven ability to build end-to-end ML pipelines and evaluate models.
• Excellent communication and collaboration across clinical and technical teams.

Responsibilities

• Own end-to-end ML development; architect data pipelines for multimodal clinical data.
• Train foundational models and deploy/monitor systems in production.
• Define quality improvement questions and publishable research with partners.
• Set engineering standards and core architectural decisions for the center.
• Bridge ML with clinical practice; translate goals into practical technical problems.
• Support recruiting and contribute to education and collaboration culture.

Skills

Cross-domain communication

Autonomy

English communication

Education

B.S./M.S. in Computer Science or Data Science

PhD in related field

Tools

Python

SQL

PyTorch

TensorFlow

Docker

Job description

NYU Grossman School of Medicine is one of the nation's top-ranked medical schools. For 175 years, NYU Grossman School of Medicine has trained thousands of physicians and scientists who have helped to shape the course of medical history and enrich the lives of countless people. An integral part of NYU Langone Health, the Grossman School of Medicine at its core is committed to improving the human condition through medical education, scientific research, and direct patient care. At NYU Langone Health, equity and inclusion are fundamental values. We strive to be a place where our exceptionally talented faculty, staff, and students of all identities can thrive. We embrace inclusion and individual skills, ideas, and knowledge.

Position Summary

We have an exciting opportunity to join our team as a Senior Research Engineer. The newly established NYU Langone Center for Orthopedic Data Science and Artificial Intelligence (CODA) is seeking a Senior Machine Learning Research Engineer to develop next-generation multimodal ML systems for musculoskeletal care. This engineer will be our first engineering hire and responsible for architectural and modeling groundwork for how we curate, model, and utilize highly unique, multimodal clinical datasets (e.g. radiographic imaging, clinical photographs, clinical videos, natural language and electronic health records). Working closely with a multidisciplinary team, you will translate complex real-world challenges into robust ML solutions and research workflows as part of an integrated bedside to bench and back approach. This is a foundational hire, with the candidate shaping our technical direction from scratch, but with the full backing of NYU Langone's data and compute infrastructure.

Infrastructure and Environment: Clinical data is primarily managed by NYU Langone's internal data team, MCIT, which will form the structured foundation for these efforts. Significant computational resources are available via our institutional high-performance supercomputing cluster. Numerous collaborating labs are available to provide infrastructure and experience. You will work directly with Dr. Jie Yao as a respected collaborator to drive the centers technical direction.

Job Responsibilities

• End-to-End ML Development: Own the full lifecycle of our early AI initiatives. You will architect data pipelines to ingest complex clinical data, train foundational machine learning models, and establish the infrastructure to securely deploy and monitor these systems.
• Research: Define critical quality improvement and research questions; and contribute to fundamental method development including statistical, machine learning, and optimization-based approaches. Pursue and co-author publishable research in collaboration with clinical and scientific partners.
• Technical Foundation: Establish the centers engineering standards. Help define best practices for code quality, implement version control, and make core architectural decisions regarding our technology stack and compute infrastructure. These early decisions will lay the groundwork for how CODA builds moving forward.
• Clinical Translation: Serve as a bridge between machine learning, clinical practice, and scientific research. Work closely with surgeons, biologists, engineers, and clinical researchers to translate ambiguous clinical workflows and research goals into concrete technical problems. Communicate model capabilities, trade-offs, uncertainty, and data limitations clearly to collaborators from diverse backgrounds while ensuring solutions remain clinically relevant, interpretable, and practical.
• Team Development: Support recruiting as the center grows. Contribute to continuing education and professional development including conferences, journal clubs, and other educational activities. Help shape a collaborative culture.

Minimum Qualifications

• Education: B.S./M.S. in Computer Science, Data Science, or related quantitative fields with 3+ years of industry or equivalent ML experience; OR a PhD in a related field (including dissertation work).
• Technical Proficiency: Strong programming skills in Python and SQL with experience working with large relational datasets (e.g. cohort construction, longitudinal analysis, or feature engineering from production or clinical databases). Expertise in modern deep learning frameworks (e.g. PyTorch and TensorFlow) and standard data processing libraries, and familiarity with containerization (e.g. Docker) and computing infrastructure.
• Systems Architecture: Proven industry experience or a strong research track record demonstrating ability to build end-of-to-end experimental pipelines, handle large, unstructured datasets, and rigorously evaluate model performance.
• Cross-Domain Communication: Exceptional collaboration and communication skills, including the ability to work effectively with clinicians, surgeons, biologists, and researchers from diverse technical backgrounds. Demonstrated ability to explain complex algorithmic trade-offs, uncertainty, modeling decisions, and data limitations to collaborators across domains. Excellent communication skills with proficiency in written and oral English.
• Autonomy: A proven ability to drive open-ended projects from initial concept to a completed, reproducible, and scalable solution.

Preferred Qualifications

• Ph.D. that includes 3+ years, including dissertation work in machine learning, computer vision, natural language processing, or a related area.
• Experience with medical imaging (XR, MRI, CT) or multimodal clinical datasets.
• Familiarity with clinical data standards (HL7, FHIR, DICOM).
• Experience working in a regulated or HIPAA-compliant environment.
• A previous publication record in ML, clinical AI, or a related field.
• Experience with high performance computing systems.

Qualified candidates must be able to effectively communicate with all levels of the organization.

Benefits

NYU Grossman School of Medicine provides a comprehensive benefits and wellness package, including financial security benefits, a generous time‑off program, employee resource groups, and a holistic wellness program focusing on physical, mental, nutritional, sleep, social, financial and preventive care.

Equal Opportunity Employer

NYU Grossman School of Medicine is an equal opportunity employer and committed to inclusion in all aspects of recruiting and employment. All qualified individuals are encouraged to apply and will receive consideration.

Salary and Transparency

Salary range: $101,493.51 - $132,088.00 annually (actual salaries depend on experience, specialty, education, and hospital need). This does not include bonuses, differential pay, or other forms of compensation.