Machine Learning Engineer Job Listing at Rockefeller University in New York, NY (Job ID 1420)

Description

Organization Overview

The newly-created Data Science Resource Center (DSRC) is responsible for supporting and advancing the research objectives of Rockefeller University's faculty and staff by providing training and consultative support in the field of data science - especially in the areas of machine learning and artificial intelligence (ML/AI).
Overview

Reporting to the Director of the Data Science Resource Center, the Machine Learning Engineer will develop core data mining, natural language processing, deep learning, and machine learning algorithms to support biological research within The Rockefeller University.  Particularly welcome are individuals with experience in computer vision tracking and/or AI in genomics.  This position provides the potential for publication in top international journals.

Responsibilities include but are not limited to the following: 

• research, implement, and deploy state-of-the-art machine learning algorithms and systems;
• build prototypes and explore conceptually innovative solutions;
• interact closely with the academic community at Rockefeller University;
• other duties and special projects as assigned.

REQUIRED QUALIFICATIONS:

BA/BS degree applicants will be only accepted if a track-record of achievement in developing AI/ML algorithms can be demonstrated. 

PREFERRED QUALIFICATIONS: 

MS degree in computer science, machine learning, electrical engineering or other related quantitative field. PhD in machine learning, computer vision or related field is preferred.

The Rockefeller University does not discriminate in employment on the basis of race, color, religion, sex (including pregnancy, gender identity), national origin, political affiliation, sexual orientation, marital status, disability, genetic information, age, membership in an employee organization, retaliation, parental status, military service or other non-merit factor. All qualified applicants will receive consideration for employment without regard to the characteristics listed above.

The salary of the finalist selected for this role will be set based on various factors, including but not limited to organizational budgets, qualifications, experience, education, licenses, specialty, and training. The hiring range provided represents The Rockefeller University's good faith and reasonable estimate of the range of possible compensation at the time of posting.

REQUIRED QUALIFICATIONS:

BA/BS degree applicants will be only accepted if a track-record of achievement in developing AI/ML algorithms can be demonstrated. 

PREFERRED QUALIFICATIONS: 

MS degree in computer science, machine learning, electrical engineering or other related quantitative field. PhD in machine learning, computer vision or related field is preferred.

The Rockefeller University does not discriminate in employment on the basis of race, color, religion, sex (including pregnancy, gender identity), national origin, political affiliation, sexual orientation, marital status, disability, genetic information, age, membership in an employee organization, retaliation, parental status, military service or other non-merit factor. All qualified applicants will receive consideration for employment without regard to the characteristics listed above.

The salary of the finalist selected for this role will be set based on various factors, including but not limited to organizational budgets, qualifications, experience, education, licenses, specialty, and training. The hiring range provided represents The Rockefeller University's good faith and reasonable estimate of the range of possible compensation at the time of posting.

Responsibilities include but are not limited to the following: 

• research, implement, and deploy state-of-the-art machine learning algorithms and systems;
• build prototypes and explore conceptually innovative solutions;
• interact closely with the academic community at Rockefeller University;
• other duties and special projects as assigned.