Senior Machine Learning Engineer

Leonardo.Ai; Wellington; Hybrid; NZD 120,000 - 150,000; Full time

Job summary

A leading AI technology company in Wellington seeks a Senior Machine Learning Engineer. In this role, you will collaborate with teams to develop and maintain infrastructures for generative AI, ensuring high-quality delivery and performance optimisation. Flexible work environment and comprehensive benefits are offered, making this role perfect for innovative minds looking to impact AI creativity significantly.

Benefits

Impact the future of AI

Reward package including equity

Inclusive parental leave policy with 18 weeks paid leave

Vibe & Thrive allowance for wellbeing

Flexible leave options including remote working abroad

Support for professional development

Fun and engaging company events

20 days annual leave

Qualifications

• Experience deploying generative models and working with optimisation techniques.
• Skilled in building automated workflows for ML models at scale.
• Strong Python skills and a focus on writing maintainable code.

Responsibilities

• Collaborate with researchers to bring new models from prototype to production.
• Build and maintain production pipelines for generative models.
• Develop and maintain automated pipelines covering training and deployment.

Skills

Generative AI Experience

MLOps Expertise

Infrastructure & Cloud

Performance & Efficiency

Data Foundations

Engineering Craft

Collaboration & Growth

Tools

AWS (S3, EC2, SageMaker)

Kubernetes

Docker

Terraform

Job description

Leonardo.Ai is building one of the world’s highest-throughput Generative AI platforms, enabling millions of users, from beginners to professionals, 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.

In this role, you’ll work at the intersection of Generative AI and MLOps. You’ll 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 have a direct and visible impact: you’ll enable teams across Leonardo to deliver AI-powered features faster, more reliably, and at scale.

What You’ll Do:

• 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.
• Flexible Work Environment: We understand the importance of work-life balance. Enjoy the flexibility to work remotely or from our vibrant offices.
• Empowering Growth: Your development is our priority. We offer continuous learning opportunities and career growth tailored to your goals.
• Impactful Work: Join us in shaping the future of AI. You'll work on innovative projects that have a meaningful impact, and your contributions will help drive advancements in AI creativity.

Leonardo.Ai Benefits:

• A range of benefits to set you up for every success in and outside of work.
• Impact the future of AI
• Reward package including equity
• Inclusive parental leave policy that supports all parents & carers with 18 weeks paid leave
• An annual Vibe & Thrive allowance to support your wellbeing, social connection, office setup & more
• Flexible leave options that empower you to be a force for good, take time to recharge and support you personally, including remote working abroad
• Support with your professional development
• Fun and engaging company events, both virtual and in-person
• 20 days annual leave

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.