Senior Machine Learning Operations Engineer (Python)
Canva’s Commitment and Mission
At Canva, we celebrate diversity. We deeply believe that bringing together diversity of thoughts, perspectives and expression is key to building the best product, team and company. We look for many different skills and abilities, as well as how you can enhance Canva and our culture. So, even if you don’t think you quite meet all of the skills listed or tick all the boxes, we’d still love to hear from you!
Our mission at Canva is to empower the world to design and since launching in 2013, we have grown exponentially, amassing over 100+ million monthly active users across 190 different countries and a team of over 3,000 people… and the best bit is that we’ve only achieved 1% of what we know we’re capable of.
Join us and design your future.
Central Platform Team (MLOps / MLInfra)
The ML Engineers working on the platform team are responsible for delivery of machine learning at scale. Our systems, frameworks and processes are used daily by ML Engineers to train, validate, deploy and monitor online inference services. We are building a platform that follows engineering best-practices and shortens the loop between early exploratory work in notebooks and shipping reliable models to production. Our platform is built using the latest technologies and cloud infrastructure.
We're looking to grow the team to continue to scale the impact of machine learning across Canva.
- Hypothesis-driven development of data and ML-driven features across Canva.
- Engineering implementation: developing and implementing ML models and features, as well as using third party APIs and pre-trained models when appropriate.
- Running offline and online experiments.
- Investigating and spiking applications of data and ML across the Canva product, considering tradeoffs between different approaches and rapidly shipping.
- Contributing to the full life cycle of ML/data models: data analysis, data preprocessing and pipeline, modelling, tuning and productization.
- Improving the scalability, speed and performance of existing models.
- Working alongside data specialists, software engineers and product owners to identify business and growth opportunities.
- Designing and creating new data workflows and deploying these workflows to users.
- Sharing and articulating statistical analysis, modelling, experiment and results to technical and non-technical audiences.
- More than 5 years of Industry experience in the machine learning /software engineering role with a Product/SaaS company.
- Experience building and deploying machine learning models. Strong understanding of end-to-end machine learning pipelines and components.
- Strong Coding proficiency in Python, interviews will be in Python.
- Familiarity with several of the following: TensorFlow, PyTorch, scikit-learn, Kubernetes, Docker, Solr/ElasticSearch
- Strong understanding of Computer Science/Engineering fundamentals and first principles covering system design, data structures, architecture, and design patterns.
- SQL experience preferred.
- Strong research skills: the ability to dig through deep learning literature and translate this into product and value for users.
Perks and Benefits
- Flexible daily working hours, we value work-life balance
- Breakfast and lunch prepared by our wonderful Vibe team
- Onsite-Gym and Yoga Membership
- End-of-Trip Facilities: Bicycle parking and showers
- Generous parental (including secondary) leave policy
- Pet-friendly offices
- Sponsored social clubs, team events and celebrations
- Relocation budget for interstate or overseas individuals (see below for visa information)
If you're seeking professional growth and enjoy working on large, distributed, cloud-based applications that delight our millions of individual and business users alike - then apply now to be considered for the position!
If you require visa sponsorship, you must ensure you have at least two (2) years of post-University commercial experience as a Software Engineer and meet the mandatory sponsorship requirements laid out by Department of Home Affairs.
We will not accept or review any CVs from external recruitment agencies.
Working at Canva
Our culture is unlike anywhere else and we design your #CanvaLife experience to empower you to do the best work of your life.
Whether you’re in the office, working from home or choosing your own adventure, our benefits for permanent Canvanauts include:
- Equity packages for you to truly be a part of the Canva journey.
- We have a hybrid work model (in-office from home), with our offices are always open to you balancing flexibility and connection
- Flexible leave so you can recharge, give back, support others or focus on your own professional development.
- Inclusive parental leave policy that supports all parents and carers throughout their parenting and caring journey.
- An annual Vibe Thrive allowance. This is for you to spend on whatever will support your wellbeing and development.. because you know what you need to Vibe and Thrive, better than anyone.
- Virtual and in-office wellness benefits including Canva University, Employee Assistant Programs and Fitness Meditation Classes.
- Canva For Good program matching your not-for-profit donations, Force for Good leave (3 paid volunteering days) and a range of sustainability and ethical initiatives to get involved in.
We make hiring decisions based on your experience, skills and passion. Please note that interviews are conducted virtually. When you apply, please tell us the pronouns you use and any reasonable adjustments you may need during the interview process.
Australia & New Zealand
Machine Learning Engineer