Canva
Machine Learning Engineer Intern (Summer 2021/22) (Dec 2021)
Opportunity expired
Opportunity details
- Internship, Clerkship or Placement
- 2 vacancies
- Apply by 30 Jul 2021
- Start date 5 Dec 2021
The Data Science specialty delivers value to Canva's users by designing, building and maintaining complex systems to apply statistics and machine learning at scale, and multiplying manual effort with data intelligence. This includes making it easy for users to discover over 75M+ templates, photos, videos and elements; messaging, marketing and building engagement with users; and making it easier for users to design.
As a Machine Learning Engineering Intern, you will have the opportunity to learn from Data Scientists and Engineers from the likes of Google, JetBrains, Yandex, Atlassian, Amazon, Facebook, and popular technology houses from all over the world. You will get the opportunity to learn and apply best-practice data science and software engineering, focused on strong software engineering fundamentals and pragmatism.
This will be perfect for you if you:
- Are currently in your final year of completing a Bachelor's or Master's degree, at any stage in your PhD, or have completed software engineering/web development certifications.
- Have strong Computing and Object-Oriented Programming (OOP) Fundamentals
- Are comfortable working in Python.
- Have the ability to conceive and translate statistical or machine learning models to practical, scalable solutions.
- Have strong verbal and written communication skills.
- Have the desire to learn and grow as a technologist.
It would be awesome if you also have:
- Experience building and deploying machine learning models.
- Experience with data platforms (e.g. Spark and Hadoop).
- Experience with machine learning frameworks (e.g. Scikit learn, TensorFlow, PyTorch).
- Experience with interactive notebooks for exploration of data and initial prototyping.
What you'll do:
- Work alongside data specialists, software engineers, product owners - to identify business and growth opportunities.
- Participate in exciting research in machine learning and data science applications across the Canva product suite.
- Improve scalability, speed and performance of existing models.
- Conceptual modeling: share and articulate modeling.
- Statistical analysis: understand and work around possible limitations in models
- Predictive modeling: most of our big data problems are towards being able to predict future outcomes.
- Hypothesis testing: develop hypotheses and test them with careful experiments.
We ensure that the Canva workspace is set up for you to do your best work and have a great time doing so, with breakout areas, little nooks and quiet places to retreat.
We have in-house chefs that whip up amazing breakfasts and lunches for the whole team, check out what's cooking at: https://www.instagram.com/canvalife/
If you're about to graduate and are seeking a truly challenging opportunity with one of the world's premier technology companies, then apply now to start the discussion with us!
Reviews
Love 85-90% of the work I get to do. 10-15% less enjoyable bureaucracy / 'keeping the lights on' work that is required.
As a backend engineer, I mainly work closely with maintaining the server, including the interaction with the database and cache. I also apply software development techniques when writing code.
I am currently working as an Associate Machine Learning Engineer. My responsibility includes maintaining existing deployed ML models in Canva and developing new ones to help users get a better experience. Sometimes it involves some data analysis as well as research.
About the employer
Canva
4.7
1,000 - 50,000 employees
Technology
Canva is a global online visual communications platform designed to empower the world to design.
Pros and cons of working at Canva
Pros
The culture and work-life balance at Canva is amazing! It helps me unlock my full working potential as I am encouraged to work at my own pace and to the best of my comfort.
Work hours are flexible as you can work at your own pace which boosts your efficiency the most. You can work fully remotely or in the office depending on your choice.
I get to work with very talented people and solve interesting problems at scale.
Free food, club activities, and events can sometimes seem too good to be true. Additionally, the company is flexible and trusting of different working schedules.
The company is extremely committed to diversity.
Cons
If you live in an area that does not have a hub or office, there will be less interaction unless you go to the office. This makes it hard for people to network and meet up regularly.
Working at a large company often means you specialise in a narrow set of tools, which can limit your exposure compared to working at a smaller startup.
Can be a fast-paced, stressful environment when launches are approaching.
Currently, I think my daily job involves much busy work without much time to understand the context.
Being remote first, although this is another really great benefit, I sometimes wish I could see my teammates more in person.