Svetlana Grant completed her MSc in Integrated Machine Learning Systems at UCL part-time while working full time and raising two young children. With a background in mobile innovation and product development, she had already been engaging with AI through online courses, but wanted a deeper, engineering-focused education to ground her understanding. The programme’s technical rigour and hands-on approach gave her just that, unlocking new possibilities in her career and preparing her for a high-impact role at one of the world’s leading AI research labs.
What inspired you to pursue an MSc in Integrated Machine Learning Systems at UCL, and how did it align with your career goals?
I had a huge interest in machine learning and AI for a few years before I applied for my part-time MSc degree in Integrated Machine Learning Systems in 2019, and completed multiple online AI courses on EdX and Coursera. I was working full time, running an innovation team, so decided that a part-time degree was my best option. When I found out that UCL was launching a new ML program I thought it was just what I needed. I wanted to focus on engineering for ML, rather than computer science, so this was a great fit in terms of the degree focus. One of the best decisions in my life.
Can you share a key learning or experience from the MSc that you’ve found particularly valuable in your career?
Doing a part-time degree while working full time, with two young children at home, was a huge commitment. But it taught me to be brave, and to ask for help. Programming was a big challenge for me as it wasn’t a normal part of my previous job. I learned to juggle things, spent evenings and weekends on my projects and coding. I also learned that having my family as my support group was crucial. There is a rephrased saying that behind every successful woman there is a supportive partner, and I agree - I could not have done it without my husband.
How did the programme prepare you for working at the intersection of AI, machine learning, and business development?
Prior to taking up the MSc degree course, I was already working in the mobile industry in innovation teams, developing new technologies and building product prototypes with partners. What I needed was a solid grounding in machine learning theory, future AI trends, and most importantly, I needed hands-on experience building my own ML models. All this became invaluable when I started my job at DeepMind.
Your career spans IoT, AI, and strategic partnerships. How has your MSc helped you navigate these fields?
My MSc gave me an excellent knowledge of these three topics, a mix of theory and practical experience. I already worked on IoT and partnerships before I started the degree but ended up taking IoT as an optional course anyway, and learned a lot from it.
What excites you most about your current role at Google DeepMind, and how does machine learning play a part in it?
I love working at Google DeepMind. I wanted to be in the room where it happens, and I am certainly working in the epicentre of building AI. There is not a day I do not learn something new. Sometimes, I feel like a kid in a sweet shop, being surrounded by some of the smartest people in the world, including recent Nobel prize winners, reading their research and helping decide who would be the best partners to create something amazing together.
What trends in AI and machine learning do you think will have the biggest impact on industry in the coming years?
I work closely with the GDM’s Robotics team and strongly believe that robotics and embodied AI will have the biggest impact on the physical world around us. I also think that AI will touch every industry, and we need to think hard about the impact we’ll be helping to make.
What advice would you give to students considering the MSc in Integrated Machine Learning Systems at UCL?
Be brave, go after big dreams, and enjoy every minute of the AI journey. UCL is an alma mater for many people who have helped to shape the AI industry, so we are in excellent company.
You’ve worked in various leadership roles. What skills from your MSc have helped you most in these positions?
I learned the value of keeping my priorities clear. No matter how hard I work, quite often there is more than I have bandwidth to do. I need to know what is important, and what is urgent, and constantly remind myself what my focus should be.
What challenges did you face transitioning from studying machine learning to applying it in a business and corporate strategy context?
My degree gave me the depth and breadth of understanding how machine learning models are built. The main next step into a commercial role was to navigate how this translated into the intricacies of data licensing and IP, writing good contracts and negotiating the terms that made each partner gain something from working together. My biggest challenge was to get comfortable with working in an environment full of uncertainty - we do a lot of things that are new, and haven’t been done before. But it also feels amazing to shape the industry.
Looking back, how has your UCL experience shaped your approach to innovation and problem-solving in your career?
My UCL degree opened the world of AI to me. There is so much change that AI will bring to the way we live and work. Studying at UCL provided me with knowledge, skills and tools to navigate the biggest change of this century.
