Interview with Deep Learning Freelancer Tuatini Godard

Interview with Deep Learning Freelancer Tuatini Godard

Interviews · Sept. 6, 2018

In this Series of Blog Posts, I talk with People that have really inspired me. People that I really look upto and that I learn and work with. Today we’re talking with Tuatini Godard. My Great Friend and an Awesome Deep Learning Freelancer from France.


This interview was done by Sanyam Bhutani, DL practitioner and RemoteML member

Sanyam:​ Hey Tuatini! Thank you for doing this interview. It’s a pleasure to have you on the blog

Tuatini: Hey Sanyam, thank you for having me!

Sanyam: You’re one of the great Freelancers I have met. Can you tell us about yourself? How do you work and what jobs do you usually take up?

Tuatini: Thanks for the compliment but I started freelancing few months ago just like you. I was an Android developer 2 years ago and I jumped in the ML/DL boat since then, learned everything I could in that field and started freelancing few months ago when I felt confident about it. I only work remotely, I can’t work next to a client looking for your every move to see if he invested his money in the right guy, it stresses me aha. I mainly target jobs which have a real purpose or which passionates me. For instance, nowadays I’m using deep learning on pathological data to automatically diagnose skin cancer.

Sanyam: Very Cool! How do you usually find work? Via Networking or Platforms?

Tuatini: Via Upwork mainly, it’s not the best place to get a lot of money but it’s ok if you’re not very good at marketing yourself like me.

Sanyam: I know you’ve been a Machine Learning Practitioner for a few months now. What got you interested?

Tuatini: I was mainly interested by AI at first. It was taught at my school when I was doing my MS but I didn’t really focus on it as opportunity in that field were… “scarce”. Then came the deep learning hype and suddenly everyone needed a deep learning expert so I jumped on the occasion as resources to learn it and opportunities were abundant. Along the way I learned about the traditional way of doing real “data science” and I kinda liked it so I’ve put aside the hype on what people call “AI” and started focusing more seriously on that very interesting field.

Sanyam: At what point did you decide to start freelancing as a ML Practitioner? What made you take the decision?

Tuatini: I had a deadline and a roadmap before I left my job as an Android developer. Here in France you can have unemployment benefits for approx 2 years so this is what I did. For a year and half / 2 years I was only focused on studying and on my roadmap. Recently I had to shift that focus to doing freelancing as I was confident enough on my skills and my unemployment benefits were about to come to an end.

Sanyam: During our offline Chats we have often discussed the difficulties of freelance work. What are some of the difficulties you face working remotely? Any downsides you would mention to the people trying to break into this space?

Tuatini: Well the first one is loneliness. When you work at home you’re on your own. Fortunately for me I have my gf around to whom I can talk to and for the current client I have I actually work with someone that I met back when I started studying deep learning so I can exchange ideas and all kind of stuff about the project with him. Most freelancer platforms put the accent on individual freelancing like freelancer.com/upwork/fiverr etc… While it’s great for an individual to get started I think it’s even better if you could do freelance mission in a team, or more like a squad of 2 or 3 people so when you’re not around your colleagues can maintain the link with your clients and you can exchange with them etc etc…

Sanyam: What would you recommend to someone starting out in the field?

Tuatini: You have to show your skill to the world, one way or another, to justify your prices. If you charge a lot of money but have no presence on the internet (no blogs/no github/no review on your profile/no kaggle profile) etc…. It will be hard for you to justify those prices. Every person is different but for me what worked was writing a blog/doing some open source projects. Kaggle is good also to show your skills, I think it’s even better than blogging/open source as everyone can see and especially understand your skills based on your kaggle profile. I mean, take a non tech potential client and give him a github vs a kaggle profile, what stands out the most to him? A bunch of line of code/projects he doesn’t understand or a bunch of straightforward badges on today’s most used platform for data science?

Sanyam: Anything else you want to share with the readers?

Tuatini: Don’t give up, data science is a multidisciplinary field and it’s hard to be good on every front. Choose a specialization at first and put all your energy on it. For instance I chose deep learning for computer vision instead of say, time series or NLP. Don’t get fooled by the AI hype like me when I started 2 years ago, there is no AI (or AGI, call it the way you want), if you choose the computer vision path, then you become a computer vision expert, for NLP you become a NLP expert. Deep learning only helps to solve a part of the big picture, it’s not the big picture itself, only a tool to add to your toolbelt. As an freelancer or an “expert” (call it the way you want) you will be asked to do more than just playing with deep learning models most of the time. Learn about data preparation, software engineering skills, some devops and co, basically the whole stack to create and ship a deep learning project in production, not just the fun part. But most importantly, learn to learn and to adapt, keep an eye on the latest trends and always stay up to date on what is going on as things moves really fast in the field of data science.

Sanyam: Thank you for the valuable insights. What would be the best place to get in touch with you or follow your activities?

Tuatini: I have a blog https://tuatini.me/ . I don’t find a lot of time to blog these days but you can find everything about me in there.

Sanyam: Thank you so much for talking doing this interview.