AI Engineer Works for an International Law Firm

Name: Anna Koroleva (she/her)

PhD: Computer Science, Université Paris-Saclay / University of Amsterdam (Joint degree), 2019

What was your main area of research?

My work addressed the problem of "spin" in biomedical publications - the situation when authors present their research results as more positive and impactful than the actual numbers show. This may be unintentional but still, it has negative consequences for the quality of healthcare. I developed Natural Language Processing (NLP) algorithms to automatically detect various potential instances of spin.

What is your current job?

I am a Senior Conversational AI Engineer for Cleary Gottlieb, based in the United Kingdom.

I work in LegalTech, and my work is a mix of data science and software development: whenever there is a potential use case for AI/NLP.

I experiment with various algorithms and models to assess the feasibility of the task and come up with a working prototype, and then I take part in writing production code to bring the new tool to the users. Basically, I write code and study data.

What is your favorite thing about your job?

I love getting to solve problems and make things work: taking a use case that has not been addressed with NLP before, and implementing a solution!

What is the most important skill you developed or experience you had during your PhD that now helps you in your current position?

Perseverance: Despite being alone in a foreign country, and working alone on a complex project, I managed to see it through until the end.

How did you build the skills necessary for your current role?

Some skills and knowledge come from as early as school: maths of course, and we had a bit of programming.

Then a Master’s in linguistics: it helps working with text data as I understand how language works, and I see patterns and exceptions to those.

But learning on the job is (unfortunately) still the best way: research projects, internships; the most useful platform for me is Omdena - a community that runs collaborative AI for Good projects: it is a tough but brilliant way to get real-life experience.

How did you find this position? What were the career steps you took to get to where you are now?

A recruiter approached me on LinkedIn (I have a somewhat visible profile thanks to Omdena)

PhD graduate ➡️ postdoctoral fellow (dropped out) ➡️ Computational Linguist ➡️ Conversational AI Engineer

If someone is interested in a similar role, what would you recommend they start doing now to prepare?

Learn maths, learn coding - via a university degree, or online courses, or even self-learning. Then try to get hands-on experience via hackathons or platforms like Omdena - that's the best way to show that you are ready for a job.

Why did you decide to not pursue a career in academia?

This was an easy decision for me. After my Master’s, I worked in industry for a few years and went to do a PhD to learn new things but also to get more visibility on the international job market. I never planned to stay in academia after the PhD.

Two main reasons: 1) academia was lonely (for me anyway), I was always working alone on my projects, and I think you get further by going with a team, like it is always the case in industry; 2) we write papers about academic projects, but they rarely actually get to be implemented and served to users, and I want to work on something practical that someone will use.

What advice do you have for someone getting their PhD and looking to pursue a career outside of academia?

People often see the academia/industry divide as some kind of line that you cross once and forever, and the decision to transition from one to another is seen as very dramatic and scary. But it does not have to be the case: you can go from academia to industry and back as much as you want, you will only be more valuable for it.

Whatever the next step is, it is just another job - it will be different to the previous one, but it does not have to be scary, and you can always change your path.