Senior Machine Learning Engineer

Summary

Join Leonardo.Ai's expanding global AI team as a Senior Machine Learning Engineer. You will play a key role in productionizing and scaling generative models, particularly diffusion-based systems, across a large fleet of GPUs. Partner with researchers, engineers, and product teams to deliver high-performance AI features used globally. This hands-on role requires tackling technical challenges at scale, from model optimization to deployment pipelines. You will contribute to one of the world’s highest-throughput GenAI systems, generating millions of images and videos daily. Leonardo.Ai offers a flexible work environment, empowering growth opportunities, and impactful work on innovative projects.

Requirements

• Generative AI Production Expertise : Proven experience deploying diffusion-based models (e.g. latent diffusion, LoRA, ControlNet) into production environments, ideally across dozens or hundreds of GPUs
• High-Performance ML Engineering : Proficiency in Python and PyTorch, with a focus on optimised inference, model tuning, and memory-efficient execution
• MLOps Fluency : Familiarity with model deployment tools and practices (e.g. model registries, workflow orchestration, CI/CD for ML)
• Real-World Systems Thinking : Comfort with performance trade-offs, debugging large-scale systems, and delivering improvements fast
• Team Collaboration : Experience working in fast-moving, cross-functional teams shipping real-world AI products
• Adaptability : Ability to pivot quickly between deep technical work, product needs, and cross-functional alignment

Responsibilities

• Deploy at Scale: Build and maintain robust production pipelines that deploy generative models, including diffusion-based systems, across multiple services, each with 100s of GPUs
• Power a Global Platform: Contribute to one of the world’s highest-throughput GenAI systems, generating millions of images and videos daily
• Optimise for Speed and Efficiency: Utilise quantisation, compilation, caching, distillation, and multi-GPU parallelism to enhance throughput, latency, and stability
• Push Model Innovation into Production: Collaborate closely with researchers to productionise new capabilities, such as LoRAs, ControlNets, and custom architectures
• Solve End-to-End Challenges: Tackle a wide range of problems — from orchestrating massive multi-GPU video pipelines to optimising end-to-end latency and hardening scalable workloads to run at global scale

Benefits

• 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 supports 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