Role overview
Grade 106
- Job Type: Officer of Administration
- Bargaining Unit:
- Regular/Temporary: Regular
- End Date if Temporary:
- Hours Per Week: 35
- Standard Work Schedule: Monday - Friday
- Building: PH-20
- Salary Range: $175,000.00 - $200,000.00
The salary of the finalist selected for this role will be set based on a variety of factors, including but not limited to departmental budgets, qualifications, experience, education, licenses, specialty, and training. The above hiring range represents the University's good faith and reasonable estimate of the range of possible compensation at the time of posting.
Position Summary
Columbia University’s Department of Biomedical Informatics is advancing innovation at the intersection of healthcare and artificial intelligence. We are seeking a highly skilled and motivated Machine Learning Engineer with expertise in generative AI. The successful candidate will play a central role in developing, validating, and deploying advanced AI models to analyze and interpret complex biomedical and clinical data. This position involves collaborating with a multi-disciplinary team of clinicians, academic researchers, software engineers, and informaticians to translate research into scalable, production-ready AI solutions that improve diagnosis, treatment planning, and patient care.
As a Machine Learning Engineer, you will play a crucial role in translating research, developing and deploying cutting-edge machine learning models to address healthcare challenges. You will be responsible for the entire lifecycle of AI projects, from data ingestion and foundational model finetuning and validation, model development and validation, and deployment. You will work collaboratively with cross-functional teams, including clinicians, academic researchers, software engineers, informaticians, and product managers, to design and implement scalable AI solutions.
What we're looking for
- Experience working with foundational models, prompt engineering, instruction tuning, in-context learning.
- Experience optimizing training pipelines for scaling novel foundation model architectures to extreme datasets and model sizes over appropriate compute resources.
- Strong programming skills in Python and experience with machine learning libraries (e.g., PyTorch, TensorFlow, scikit-learn) as well as visualization packages.
- Experience with cloud platforms (e.g., Azure, Databricks, AWS, GCP) is a plus.
- Experience with version control systems (e.g., Git) and continuous integration/continuous deployment (CI/CD) pipelines.
- Experience working with clinical data is a plus.
- Excellent analytical and problem-solving skills.
- Strong communication and collaboration skills.
Equal Opportunity Employer / Disability / Veteran
Columbia University is committed to the hiring of qualified local residents.