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Machine Learning Engineer

Machine Learning Engineer

black.aiWorkFromHome, Canterbury, New Zealand
12 hours ago
Job description

Location

New Zealand (Remote), Auckland (Remote), Hamilton (Remote), Tauranga (Remote), Wellington (Remote), Christchurch (Remote)

Employment Type

Full time

Location Type

Remote

Department

Engineering

About Us

About Us

Leonardo.Ai is building one of the world’s most advanced generative‑media platforms, empowering millions of people to turn ideas into high‑quality images and videos in seconds.

Now part of the Canva family, we’re scaling our global R&D team to make creativity faster, smarter, and more accessible for everyone.

The Role

We’re looking for a Machine Learning Engineer who enjoys working hands‑on across model development and ML systems, someone who wants to learn, ship real features, and grow in a high‑context, collaborative environment.

You’ll join the AI Engineering team inside the Platform Tribe, where we build the training pipelines, inference systems, and model‑serving tooling that help teams across Leonardo deliver reliable AI‑powered creative experiences at scale.

Your work will support features such as high‑fidelity image generation, stylisation workflows, and emerging image‑to‑video capabilities, helping turn cutting‑edge research into creative tools people use every day.

This role offers deep exposure to generative ML, including diffusion and transformer models, while developing your confidence in performance optimisation, GPU environments, and reproducible workflows. You’ll work alongside senior ML engineers and research scientists, gaining context and stepping into more ownership as you grow.

If you’re excited about generative media and want to sharpen both your modelling and engineering depth, you’ll thrive here.

What You’ll Do

Model Development and Evaluation

Collaborate with research scientists to adapt and fine‑tune diffusion and transformer‑based models.

Run experiments and evaluate model outputs to improve quality and consistency.

Contribute to performance improvements such as batching, caching, or quantisation with guidance.

Help identify bottlenecks and opportunities for generation improvements.

ML Engineering and Systems Development

Build and maintain training and inference pipelines.

Work with GPU environments on AWS and Kubernetes.

Use Docker and internal tools to standardise training, experimentation, and deployment.

Contribute to shared APIs and model‑serving components.

MLOps and Reliability

Support dataset handling, experiment tracking, and model versioning.

Extend monitoring dashboards and alerts to maintain system performance.

Maintain reproducibility across checkpoints, datasets, and experiments.

Cross‑Team Collaboration

Work with product teams to support integration of generative features.

Share learnings and contribute to a supportive engineering culture.

Skills We Value

Strong Python engineering skills and familiarity with ML workflows.

Experience with PyTorch or TensorFlow in project, research, or production settings.

Understanding of model training or fine‑tuning.

Interest in improving inference performance and efficiency over time.

Clear, thoughtful communication and collaborative working style.

Curious and comfortable learning in unfamiliar technical areas.

Nice to Have

Exposure to diffusion, transformer, or video generation models.

Familiarity with AWS, Docker, Kubernetes, or GPU orchestration.

Experience with monitoring or observability tooling.

Open‑source, research, or personal ML project contributions.

Background in creative‑tech, ML tooling, or SaaS environments.

Why You’ll Love Working Here

You’ll be building technology that directly enables human creativity at scale, not just optimising models in isolation, but shaping how real people express ideas, tell stories, and create art. You’ll join a team that values thoughtful engineering, shared context, and steady growth over ego or heroics. There is room to explore, room to ask questions, and room to develop depth in the areas that genuinely interest you. We work with curiosity, we build with care, and we learn from each other as we go.

Our Culture :

Inclusive Culture : We celebrate diversity and are committed to creating an inclusive environment where everyone feels valued and empowered. At Leonardo AI, your unique perspectives and experiences are welcomed and essential to our success.

Flexible Work Environment : We understand the importance of work‑life balance. Enjoy the flexibility to work remotely or from our vibrant offices. We have employees all over New Zealand, ensuring you can thrive personally and professionally.

Empowering Growth : Your development is our priority. We offer continuous learning opportunities and career growth tailored to your goals. You’ll be encouraged to grow and excel in your career at Leonardo AI.

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. Here's a taste of what's on offer :

Impact the future of AI

Reward package including equity - we want our success to be yours too

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

#J-18808-Ljbffr

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Machine Learning Engineer • WorkFromHome, Canterbury, New Zealand

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