Senior Machine Learning Engineer

Overview
Senior Machine Learning Engineer role at
Leonardo.Ai
.
Leonardo.Ai is building one of the world's highest-throughput Generative AI platforms, enabling millions of users to create high-quality images and videos with ease. Now part of the Canva family, we're growing our global R&D team to deliver AI tools, products, and infrastructure that make creativity limitless for nearly a quarter of a billion users.
The Role:
We're looking for a Senior Machine Learning Engineer to join our Platform Tribe, the team that provides the tools, infrastructure, and expertise that help every other product team at Leonardo move faster. You'll work at the intersection of Generative AI and MLOps, partner with researchers and engineers, be embedded in other teams for high-impact projects, and help design the pipelines, GPU infrastructure, and automation that transform cutting-edge research into production-ready features, making creativity accessible to millions of people. Your work will enable teams across Leonardo to deliver AI-powered features faster, more reliably, and at scale.
What You'll Do
Generative AI & Inference:
Collaborate with researchers to bring new models from prototype to production and ensure they deliver meaningful value.
Build and maintain production pipelines for diffusion-based and related generative models (e.g. LoRA, ControlNet).
Optimise inference for speed, reliability, and efficiency using techniques such as quantisation, distillation, caching, and multi-GPU parallelism.
Tackle complex challenges like orchestrating multi-GPU video pipelines while ensuring systems are intuitive and maintainable.
MLOps & Infrastructure
Develop and maintain automated MLOps pipelines covering training, deployment, monitoring, and retraining.
Build CI/CD workflows for machine learning that make handovers from research to production seamless and safe.
Create scalable data pipelines and storage solutions to support high-throughput workloads.
Set up clear monitoring and alerting for model performance (e.g. Prometheus, Grafana, CloudWatch).
Design secure, reliable infrastructure on AWS (S3, EC2, SageMaker) using Infrastructure-as-Code tools like Terraform.
Platform Acceleration
Be embedded in other teams, from Generations to Enterprise, to support high-impact projects requiring deep ML expertise.
Develop shared tooling, reusable workflows, and architecture patterns that help teams across Leonardo build and ship faster.
Promote knowledge-sharing, best practices, and scalable solutions across the organisation.
Skills We Love
Generative AI Experience: Experience deploying diffusion-based or similar generative models into production and working with inference optimisation techniques.
MLOps Expertise: Skilled in building automated, reliable workflows for training, deploying, and monitoring ML models at scale.
Infrastructure & Cloud: Hands-on with AWS (S3, EC2, SageMaker), Kubernetes, Docker, and Infrastructure-as-Code (Terraform).
Performance & Efficiency: Proficient in techniques such as quantisation, distillation, caching, and distributed inference.
Data Foundations: Ability to design scalable data pipelines and storage solutions (SQL/NoSQL).
Engineering Craft: Strong Python skills and a focus on writing clear, maintainable, and collaborative code.
Collaboration & Growth: Thrive in cross-functional teams, value open feedback, and enjoy supporting others' success while learning continuously.
Our Culture
Inclusive Culture: We celebrate diversity and are committed to creating an inclusive environment where everyone feels valued and empowered. Your unique perspectives and experiences are welcomed and essential to our success at Leonardo AI.
Flexible Work Environment: Remote or office work options; employees across Australia.
Empowering Growth: Continuous learning opportunities and career growth tailored to your goals.
Impactful Work: Work on innovative projects that have meaningful impact and drive advancements in AI creativity.
Leonardo.Ai Benefits
Benefits to support success in and outside of work, including equity, parental leave, wellbeing allowances, flexible leave options, professional development support, and more.
Equity reward package
18 weeks paid parental leave
Annual wellbeing allowance for wellbeing, social connection, and office setup
Flexible leave options and remote work abroad
20 days annual leave
Please apply
We're realistic about experience, even if you haven't worked at this scale before. We encourage anyone exposed to deploying generative models to production, working with techniques like LoRA or diffusion, and optimising inference across GPUs to apply for this role.
Seniority level
Mid-Senior level
Employment type
Full-time
Job function
Engineering and Information Technology
Industries
Technology, Information and Internet
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