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Job ID: 249394

Senior Research Engineer - Machine Learning Systems
University at Buffalo, The State University of New York


Date Posted Nov. 21, 2024
Title Senior Research Engineer - Machine Learning Systems
University University at Buffalo, The State University of New York
Buffalo, NY, United States
Department Institute for Artificial Intelligence & Data Sciences
Application Deadline Open until filled
Position Start Date Available immediately
 
 
  • Professional Staff
  • Research/Technical/Laboratory
 
 
UB is seeking a Senior Research Engineer with deep expertise in areas such as Artificial Intelligence (AI)/machine learning, AI engineering, AI infrastructure, hybrid cloud computing, and parallel programming with GPUs, to work at the Institute for Artificial Intelligence and Data Science (IAD). As a Senior Research Engineer, you should be experienced in the development of scalable AI systems and deployment of distributed ML models, and will be expected to collaborate with researchers across domains. This role includes opportunities to work with state-of-the-art natural language processing, large language models (LLMs), computer vision models, speech models, time series models, and many other related machine learning models, managing AI infrastructure, and optimizing distributed model training and inference.

The IAD at the University at Buffalo is a leader in advancing AI, data science, and computational research. IAD fosters innovation by addressing pressing challenges in areas such as education, health care, robotics, and autonomous vehicles, contributing to the future of the U.S. economy and security. This role offers the opportunity to contribute to UB’s pioneering work at the intersection of AI and data science, collaborating with experts to drive advancements that make a lasting societal impact.

Key Responsibilities:
  • Design and develop full-stack end-to-end AI solutions to support IAD’s missions.
  • Collaborate with UB’s various decanal units to understand the requirements of AI solutions and build the solutions accordingly.
  • Lead system architecture discussions and the design of the full-stack solution architecture, including front-end, back-end, and cloud deployment (such as AWS, GCP).
  • Design, maintain, and optimize AI infrastructure to support the test and deployment of AI solutions, including distributed ML training and inference.
  • Under the guidance of faculty members, work with and deploy machine learning models (including LLM models) into both on-prem systems and hybrid clouds, ensuring efficient integration into production environments.
  • Build and maintain scalable, real-time data pipelines and MLOps workflows.
  • Mentor junior engineers to build the AI solutions with robust system performance.

Outstanding Benefits Package
Working at UB comes with benefits that exceed salary alone. There are personal rewards including comprehensive health and retirement plan options. We also focus on creating and sustaining a healthy mix of work, personal and academic pursuit - all in an effort to support your work-life effectiveness. We support your growth and development through our career coaching and training department and we qualify as a public service loan forgiveness organization. Learn more about our benefit packages.

About The University at Buffalo
The University at Buffalo (UB) #ubuffalo is one of America’s leading public research universities and a flagship of the State University of New York system, recognized for our excellence and our impact. UB is a premier, research-intensive public university dedicated to academic excellence. Our research, creative activity and people positively impact the world. Like the city we call home, UB is distinguished by a culture of resilient optimism, resourceful thinking and pragmatic dreaming that enables us to reach others every day. Visit our website to learn more about the University at Buffalo.
 
As an Equal Opportunity / Affirmative Action employer, the Research Foundation will not discriminate in its employment practices due to an applicant’s race, color, religion, sex, sexual orientation, gender identity, national origin and veteran or disability status.

 
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