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Research Programmer

Job in New Brunswick, Middlesex County, New Jersey, 08933, USA
Listing for: Rutgers, The State University of New Jersey
Full Time position
Listed on 2026-10-12
Job specializations:
  • IT/Tech
    Machine Learning/ ML Engineer, AI Engineer (Applied/Software), Data Scientist
Salary/Wage Range or Industry Benchmark: 120000 - 130000 USD Yearly USD 120000.00 130000.00 YEAR
Job Description & How to Apply Below
Position Details
Position Information
Recruitment/Posting Title Research Programmer Department Quantitative  Biomedicine Inst Salary Details $120,000 - $130,000

Offer Information The final salary offer may be determined by several factors, including, but not limited to, the candidate’s qualifications, experience, and expertise, and availability of department or grant funds to support the position. We also take into consideration market benchmarks, if and when appropriate, and internal equity to ensure fair compensation relative to the university’s broader compensation structure. We are committed to offering competitive and flexible compensation packages to attract and retain top talent.

Benefits Rutgers provides a comprehensive benefits package to eligible employees. The specific benefits vary based on the position and may include:

Medical, prescription drug, and dental coverage

Paid vacation, holidays, and various leave programs

Competitive retirement benefits, including defined contribution plans and voluntary tax-deferred savings options

Employee and dependent educational benefits (when applicable)
Life insurance coverage

Employee discount programs

Posting Summary The Rutgers Artificial Intelligence and Data Science (RAD) Collaboratory is seeking one or more Research Programmers to support leveraging modern Machine Learning (ML) and Deep Learning (DL) techniques by Rutgers faculty, postdoctoral fellows, and students. The ideal candidate will have a strong ML/DL and cyberinfrastructure (CI) background and a willingness to contribute to interdisciplinary research across diverse basic and applied science and engineering domains.

Responsibilities will include:
Design, develop, and deploy ML/DL algorithms for domain science and engineering fields Support RAD Collaboratory research on national cyberinfrastructure (e.g., ACCESS, NAIRR, and DOE supercomputers) or cloud environments (e.g., AWS, GCP, and Azure) Support application of ML/DL/CI techniques across topics and domains Deliver training on ML/DL/CI techniques and best practices to a broad range of researchers Stay at the forefront of new ML/DL techniques and ML/DL systems that support science and engineering research Co-author peer-reviewed interdisciplinary research publications Contribute to funding applications from external sources (e.g., NSF, NIH)
Position Status Full Time Posting Number
25FA0745

Posting Open Date
08/01/2025

Posting Close Date
Qualifications

Minimum Education and Experience Ph.D. in computer science, engineering, or other related research fields with a strong background in applied ML/DL in interdisciplinary research.

Experience working with ML/DL platforms and algorithms.

Track record of working with domain experts, researchers, and stakeholders to support diverse science and engineering applications.

Certifications/Licenses Required Knowledge, Skills, and Abilities

Experience with DL frameworks such as PyTorch, Deep Speed, Accelerate, or Megatron-LM

Experience with large language model (LLM) techniques such as supervised fine-tuning, retrieval augmented generation, and in-context learning Advanced Statistical Analysis:
Proficiency in advanced statistical techniques and probability theoryGPU Programming:

Experience with GPU programming and optimization for ML models, utilizing frameworks, like CUDA or OpenCL

Experience with applied computer vision, such as convolutional neural networks and vision transformers is preferred Experience in deploying open-source and open-data DL projects at scale and job management with SLURM or PBS is preferred Knowledge of software engineering and MLOps (e.g., CI/CD workflow) is preferred Familiarity with scientific or ML workflows is preferred Training or tutorial experience for domain…
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