The University of Virginia seeks applicants for a Deep Learning Research Scientist to join the Research Computing team. Deep Learning, and AI in general, are used in research for multiple disciplines.  As a member of the Research Computing team, you will support research projects in a variety of disciplines by developing and applying innovative deep-learning algorithms to large datasets. 

RC is within UVA Information Technology Services (ITS) at UVA.  ITS is a phenomenal place to lead, grow, and deliver impact. It's an organization that values results and teamwork. The team strives to create a welcoming, supportive workplace in an agile group where everyone feels empowered to be their authentic selves and share ideas. We embrace a commitment to diversity, equity, and inclusion. ITS values work-life balance and provides flexible work location options where possible. Please see additional information about joining our team.

What You'll Do 

You will work with researchers at the University to apply artificial intelligence (AI), machine learning (ML), and deep learning (DL) to the researchers’ data.  Where applicable, you may develop new algorithms for DL. You should have a solid knowledge and understanding of AI methods for applications, such as generative AI, large language models, computer vision, image and video processing, speech recognition, and speech enhancement. You will work as part of a team on the application of AI/ML/DL systems and algorithms, as well as the implementation, and the optimization or parallelization of the algorithms on our high-performance cluster (HPC). 

Location: Hybrid, working onsite at our Charlottesville office as needed.

As a staff member of the Data Analytics Center, you will provide the following support to UVA faculty:

• Collaborate with interdisciplinary teams to apply AI solutions to complex research problems.

• Oversee and manage your efforts on AI-based projects, ensuring timely completion and scientific rigor.

• Prepare presentations and technical reports that reflect your results.
   

Also, within the Data Analytics Center, you will have the opportunity to 

• Research and develop algorithms (as needed to support faculty) for AI/ML/DL systems, generative AI, Large Language Models (LLMs), diffusion models, neural rendering, speech or vision processing. 

• Provide training and workshops on AI and deep learning techniques for the university community.

• Mentor and guide junior researchers and team members in AI methodologies.

• Optimize AI algorithms and neural networks for our HPC system, which may include parallel implementations. 

• Stay current on the latest developments in AI and machine learning.

Required Qualifications:

• An advanced degree and at least 5 years of related work experience

• Proven expertise in AI systems and learning algorithms. 

• Strong analytical and problem-solving skills. 

• Excellent communication and writing skills. 

• Inclusive – you are able to adapt to working with diverse researchers and disciplines.

• ·vid learner – you demonstrate curiosity and persistence when faced with challenging projects and actively explore new ideas or approaches.

• Collaborative – you are able to build relationships with researchers and our team members, offering support and welcoming new approaches. 

​Preferred Qualifications

• PhD in Computer Science, Electrical Engineering, Data Science, or a related field with a focus on AI/DL. 

• 10-20+ years of experience in research. 

• Solid understanding of AI applications such as generative AI, LLMs, computer vision, and speech processing. 

• Coding skills in popular deep learning frameworks, such as PyTorch and TensorFlow. 

Anticipated Hiring Range: $140,000 - $160,000 / annual

 This is a restricted position that has committed funding through June 2028, continuation is dependent on the availability of funding.

Benefits Include: The choice between 3 different health plans; vision and dental insurance; life insurance; benefits savings accounts; starting with 22 days of paid time off a year in addition to 12 or more paid holidays; 8 weeks of paid parental leave; short term disability; up to $5,250 after your first year for combined use of tuition toward a degree-seeking program or up to $2,000 for professional development including classes, certification training and conferences; and more!

The selected applicant will be required to complete a background check prior to their first day of employment per university policy.

TO APPLY:

Please visit UVA job board: https://jobs.virginia.edu/us/en/ and search for R0057078

Complete an application online and attach:

·        Cover Letter

·        Resume

PROCESS FOR INTERNAL UVA APPLICANTS: Please apply through your Workday Home page, search “Find Jobs”, and search for R0057078

***Please note that you MUST upload ALL documents into the CV/Resume box. Applications that do not contain all of the required documents will not receive full consideration. ***

For questions about the application process, please contact Bill Crane, ITS Recruiter at xer5ff@virginia.edu

For more information about UVA and the Charlottesville community please see  www.virginia.edu/life/charlottesville  and https://embarkcva.com/

Physical Demands:

This is primarily a sedentary job involving extensive use of desktop computers. The job does occasionally require traveling some distance to attend meetings, and programs.

The University of Virginia, including the UVA Health System which represents the UVA Medical Center, Schools of Medicine and Nursing, UVA Physician’s Group and the Claude Moore Health Sciences Library, are fundamentally committed to the diversity of our faculty and staff.  We believe diversity is excellence expressing itself through every person's perspectives and lived experiences.  We are equal opportunity and affirmative action employers. All qualified applicants will receive consideration for employment without regard to age, color, disability, gender identity or expression, marital status, national or ethnic origin, political affiliation, race, religion, sex (including pregnancy), sexual orientation, veteran status, and family medical or genetic information.