Influential Woman · Technology
Victoria Washington
Python
Data Labeling Analyst, Tundra
Fort Mitchell, AL 36856
Her Story
About Victoria
Victoria Washington is a Data Labeling Analyst at Tundra, as well as a Data Analyst with seven years of experience in the technology field, including one and a half years specializing in data labeling and artificial intelligence-focused work. In her current role, she supports the development and refinement of AI systems by ensuring data accuracy, model reliability, and adherence to safety and quality standards. Her work is grounded in a strong commitment to AI safety, helping ensure that systems produce responsible and trustworthy outputs in real-world applications. Throughout her career, Victoria has developed a strong focus on artificial intelligence safety and ethical system use. She has contributed to initiatives aimed at identifying and addressing potentially harmful or unsafe model behavior within digital environments, including efforts that involved detecting concerning models and supporting their swift removal from online platforms. She is currently pursuing a Master of Science in Artificial Intelligence and Data Analytics at Villanova University, with an expected completion in spring 2028, further strengthening her expertise in machine learning, analytics, and responsible AI development. Victoria’s professional journey reflects a blend of creativity, adaptability, and self-directed technical growth. Originally trained in music at the university level, she transitioned into technology through early exposure to computer science and extensive hands-on learning in the field. Over time, she has built a solid foundation in data analysis, AI training, and talent coordination. She remains committed to the belief that artificial intelligence is a tool designed to enhance human capability, and she advocates for its responsible and balanced use as the industry continues to evolve.
Her Interview
Ten minutes with Victoria
01What do you attribute your success to?
I attribute my success for sure to my family. I am one of 8 children, and we have some brilliant minds - all brilliant minds. All of my siblings are extremely brilliant. My oldest sister is a doctor, and My other older sister studied psychology and has teaching experience in higher education, and my older brother works in GIS, and all of them are extremely, extremely talented and amazing, and I think that I just want to be like them. So they inspire me a lot. My parents really poured a lot of 'you guys can do anything you put your mind to' into us, and if you ask my dad, all of us are geniuses, no matter what.
02What’s the best career advice you’ve ever received?
My older sister, Dr. Janique Walker, who works at Coppin State University, told me very clearly that as a Black woman, everybody is going to tell me that I'm not going to do anything, I'm not going to achieve anything, because that's the expectation that's put on me. She told me that not only when it comes to work should I put my best foot forward in everything that I do, but that I should walk into rooms like the room was built for me. No matter how I feel about that, no matter what other people might look at me as, whatever the case may be, if I walk into the room, that room was built for me, and the room can crumble when I leave, but right now, that room is for me. I have always kept that to my heart. I take it very seriously, because I see who she is and how she moves, and she does amazing things. It's a trickle-down effect, because like I said, there's 8 of us. I see that she's effectively poured into all of us, and I know she got that from our parents.
03What advice would you give to young women entering your industry?
Number one, don't be scared of the boys. This is a male-dominated field - I just got my first Black woman on my team since I started working here, and she's one of four women total. When I first joined, it was just me. So don't be scared of the boys. You're just as competent as everybody else. And don't let them make things seem super technical, where you have to know this and you have to know that. No, you don't. It's okay to be like, hey, I don't quite understand this, because people do go out of their way to make you uncomfortable as a woman, they do. Or to dumb things down for you, because they just assume you don't understand, which has happened plenty of times. So don't be scared to go in the room and do what you're supposed to do.
04What are the biggest challenges or opportunities in your field right now?
The challenges are that it's hard to move up. It's very difficult to progress, at least within my current scope and understanding. It's kind of hard to move from one position to another. There's a lot of people struggling to just get a new job or to move up in this industry. Another challenge is that there's a lot of layoffs at AI companies, almost constantly. I actually was working two jobs, and they just did a massive layoff and got rid of my entire department pretty much, which blew my mind. But I think the opportunity there is that there's always room to grow when it comes to your knowledge. You can be self-taught when it comes to coding, and you can build your own models, and there's room for you to become better without needing to work a traditional job. And if you're very good at it, you can become the traditional job.
05What values are most important to you in your work and personal life?
In my personal life, obviously my faith, but then also having time. I cannot function unless I feel like I have time - time management altogether. I don't like being rushed. Give me time, give me space, give me time to breathe, give me time to pray, get my head together. And then at work, I value accuracy and efficiency over everything. If I'm working with a model, and this model is just not performing well, I am the first one to be like, fix it! We gotta fix it, and I want it done quickly. I want it done as fast as we possibly can. Obviously, take your time when things need to be done - quality over quantity - but if I spot it on Monday, by Thursday, I want to see progress.
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