Research Engineer - Evaluations
Research Engineer - Evaluations

Research Engineer - Evaluations

City of London Full-Time 36000 - 60000 ÂŁ / year (est.) No home office possible
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Canva

At a Glance

  • Tasks: Engineer AI agents to evaluate generative design models and enhance user experience.
  • Company: Join Canva, a leader in design innovation with a vibrant culture.
  • Benefits: Equity packages, flexible leave, and a wellbeing allowance for a balanced life.
  • Why this job: Make a real impact on design technology that empowers millions of users.
  • Qualifications: Strong understanding of generative AI and experience with machine learning frameworks.
  • Other info: Flexible work options and a supportive, inclusive environment await you.

The predicted salary is between 36000 - 60000 ÂŁ per year.

Company Description

Join the team redefining how the world experiences design.

Thanks for stopping by. We know job hunting can be a little time consuming and you\\u2019re probably keen to find out what\\u2019s on offer, so we\\u2019ll get straight to the point.

Where and how you can work

Our flagship campus is in Sydney, Australia, but London and Austria are home to part of our European operations. And you have choice in where and how you work, we trust our Canvanauts to choose the balance that empowers them and their team to achieve their goals.

Job Description

At Canva, our mission is to empower the world to design. To ensure our generative AI models are truly helpful, we are seeking a talented Research/Machine Learning Engineer to build our next-generation evaluation system by leveraging automatic evaluations.

About the role

You will engineer sophisticated AI agents that can automatically assess the quality and human alignment of our generative design models. This high-impact role focuses on building the practical systems that make cutting-edge research effective, to provide a rapid feedback loop that guides the future of design generation at Canva, ultimately empowering millions of users to create.

At the moment, this role is focused on:

  • Agentic Evaluation Systems: Engineering autonomous AI agents that use Multimodal Large Language Models (MLLMs) to evaluate the quality, relevance, and human alignment of generated designs.
  • Inference-Time Alignment: Mastering techniques that improve model outputs without full retraining, but by inference-based methods including prompt engineering, in-context learning and Retrieval-Augmented Generation (RAG).
  • Model Benchmarking & Analysis: Building a rigorous framework to systematically benchmark internal and external quality understanding models, delivering clear, data-driven insights on human alignment.

Primary Responsibilities

  • Design, build, and optimize the infrastructure for an \”MLLM-as-a-Judge\” evaluation system for scalable, automated feedback.
  • Implement and experiment with inference-time alignment techniques (Prompt Engineering, RAG, ICL) to directly improve model output quality.
  • Establish and manage a comprehensive benchmarking process to compare various foundation models on design-centric tasks.
  • Analyze evaluation data to identify model failure modes and provide actionable recommendations to the research team.
  • Collaborate with research scientists and ML engineers to integrate the agentic judge system into the model development lifecycle.
  • Translate the latest research in LLM evaluation and agentic AI into practical, production-ready engineering solutions.

You\’re probably a match if you

  • You have a strong understanding of generative AI models (e.g., Diffusion Models, GANs, Transformers) and their architectures, with practical experience that informs robust evaluation strategies
  • Excel at creating data-driven evaluation methodologies, turning user analytics into clear, actionable insights.
  • You\’ve successfully managed or optimized large-scale distributed model training across hundreds of GPUs
  • You have a solid understanding of machine learning, have worked with PyTorch and know how to optimize such codes for speed
  • You have disciplined coding practices, and are experienced with code reviews and pull requests.
  • You have experience working in cloud environments, ideally AWS

Nice to Have

  • Familiarity with evaluation libraries and frameworks.
  • Experience building or working with agentic AI systems or multi-agent coordination.
  • Knowledge of data visualization tools to communicate findings effectively.
  • A background or interest in human-computer interaction, design principles, or AI ethics.

Qualifications

Additional Information

What\\u2019s in it for you?

Achieving our crazy big goals motivates us to work hard – and we do – but you\\u2019ll experience lots of moments of magic, connectivity and fun woven throughout life at Canva, too. We also offer a stack of benefits to set you up for every success in and outside of work.

Here\\u2019s a taste of what\\u2019s on offer

  • Equity packages – we want our success to be yours too
  • Inclusive parental leave policy that supports all parents & carers
  • An annual Vibe & Thrive allowance to support your wellbeing, social connection, home office setup & more
  • Flexible leave options that empower you to be a force for good, take time to recharge and supports you personally

Check out lifeatcanva.com for more info.

Other stuff to know

We make hiring decisions based on your experience, skills and passion, as well as how you can enhance Canva and our culture. When you apply, please tell us the pronouns you use and any reasonable adjustments you may need during the interview process.

Please note that interviews are predominantly conducted virtually.

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Research Engineer - Evaluations employer: Canva

At Canva, we pride ourselves on fostering a vibrant and inclusive work culture that empowers our employees to thrive both personally and professionally. With flexible working arrangements, generous equity packages, and a strong focus on wellbeing, our Sydney campus offers a dynamic environment where creativity and innovation flourish. Join us to be part of a team that values collaboration, supports growth, and is dedicated to redefining the design experience for millions around the globe.
Canva

Contact Detail:

Canva Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Research Engineer - Evaluations

✨Tip Number 1

Network like a pro! Reach out to people in the industry, especially those at Canva. A friendly chat can open doors and give you insights that a job description just can't.

✨Tip Number 2

Prepare for your interview by diving deep into generative AI models. Brush up on your knowledge of MLLMs and be ready to discuss how you can contribute to building evaluation systems.

✨Tip Number 3

Showcase your projects! If you've worked on relevant AI or machine learning projects, make sure to highlight them during interviews. Real-world examples can set you apart from the crowd.

✨Tip Number 4

Don't forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you're genuinely interested in joining the Canva team.

We think you need these skills to ace Research Engineer - Evaluations

Generative AI Models
Multimodal Large Language Models (MLLMs)
Prompt Engineering
In-Context Learning (ICL)
Retrieval-Augmented Generation (RAG)
Model Benchmarking
Data Analysis
Machine Learning
PyTorch
Distributed Model Training
Cloud Environments (AWS)
Evaluation Methodologies
Human-Computer Interaction
Data Visualisation Tools

Some tips for your application 🫡

Show Your Passion for AI: When writing your application, let us see your enthusiasm for generative AI models. Share any projects or experiences that highlight your understanding and passion for this field. We love seeing candidates who are genuinely excited about what they do!

Tailor Your Application: Make sure to customise your application to align with the job description. Highlight relevant skills and experiences that match the role of Research Engineer - Evaluations. This shows us that you’ve done your homework and are serious about joining our team.

Be Clear and Concise: Keep your application straightforward and to the point. Use clear language to describe your experiences and achievements. We appreciate a well-structured application that makes it easy for us to see why you’d be a great fit for the role.

Apply Through Our Website: Don’t forget to submit your application through our website! It’s the best way for us to receive your details and ensures you’re considered for the position. Plus, it’s super easy to do!

How to prepare for a job interview at Canva

✨Know Your Stuff

Make sure you brush up on generative AI models and their architectures. Familiarise yourself with concepts like Diffusion Models, GANs, and Transformers. Being able to discuss these topics confidently will show that you're not just a candidate, but someone who understands the core of what Canva is all about.

✨Showcase Your Experience

Prepare specific examples from your past work where you've successfully managed or optimised large-scale distributed model training. Highlight your experience with PyTorch and any cloud environments like AWS. This will demonstrate your hands-on skills and how they align with the role.

✨Data-Driven Mindset

Be ready to talk about how you've created data-driven evaluation methodologies in previous roles. Bring examples of how you've turned user analytics into actionable insights. This will resonate well with Canva's focus on delivering clear, data-driven insights.

✨Collaborative Spirit

Canva values collaboration, so be prepared to discuss how you've worked with research scientists and ML engineers in the past. Share experiences where you integrated systems into the development lifecycle, as this will highlight your ability to work effectively within a team.

Research Engineer - Evaluations
Canva
Location: City of London
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