Machine Learning Engineer

Machine Learning Engineer Join to apply for the Machine Learning Engineer role at Leonardo.Ai 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, ask questions, and 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. 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 success. Impact the future of AI. Reward package including equity. Inclusive parental leave policy with 18 weeks paid leave. An annual Vibe & Thrive allowance to support wellbeing, social connection, office setup & more. Flexible leave options, including remote working abroad. Support with professional development. Fun and engaging company events, both virtual and in‑person. 20 days annual leave. #J-18808-Ljbffr