Dr. Nashlie Sephus is an applied scientist working on the Amazon Web Services machine learning team. According to an Amazon Science profile, Sephus is responsible for establishing scientifically rigorous benchmarking and testing methods for machine learning services like Amazon Rekognition, ensuring that the technology produces results that are highly accurate and fair.

“I’m a black woman with a southern accent who has been immersed in machine learning technologies as both a scientist and a consumer," she told Amazon Science in April 2020. "I have a personal interest in making sure these technologies are developed and deployed accurately and responsibly. I also want to ensure that the people in my community are in-the-know about the technology and the important topics surrounding it. I’m dedicated to identifying potential blind spots.”

On September 11, 2020, Sephus posted an announcement on Facebook that she had bought twelve acres and seven buildings in a new venture worth $25 million. Banks wouldn’t loan her the money, but the property owner agreed to a short-term finance deal.

"Today was the culmination of over 18 months, 12 acres, 7 buildings, 2 downtown districts, 3 unwilling to do loan banks (we’ll address this later), a committed team, a lot of dollars, a solid group of lawyers, and a lot of patience and grit to invest in my hometown of Jackson, Mississippi, bringing technology access for all. Excited for the journey that's about to come!⁣ 🙌🏾⁣ "

“I think it’s really important for me to give back to the community that helped shape me and I always love to see people get enthused and exposed to technology and so I wanted to make that process a little bit easier,” she told WLOX.

According to Sephus's bio on LinkedIn, she received her Ph.D. from the School of Electrical and Computer Engineering (ECE) at the Georgia Institute of Technology in 2014, after which she started a position with Exponent consulting firm in New York City. Her core research areas were digital signal processing (mainly music, speech, and image signals), machine learning, and computer engineering/science. She received her B.S. in Computer Engineering from Mississippi State University (2007).

She’s had several internships and research experiences with companies and research labs, such as IBM, Delphi, University of California at Berkeley, GE Research Center, GE Energy, and Kwangwoon University in Seoul, South Korea.