Chaos

Machine Learning Engineer

• Design, develop, and optimize machine learning models in one or more solutions, including asset generation and capture, render enhancement, scene intelligence, agentic design workflows, and intuitive design interactions.
• Investigate and bring techniques from a variety of AI research areas, such as diffusion, super-resolution, conditioned generation, plus neural and differentiable rendering, into artists’ hands.
• Evaluate, integrate, and orchestrate off-the-shelf third-party foundation models to accelerate feature development and deployment.
• Mentor other engineers and contribute to the growth of the team’s knowledge and expertise in machine learning.
• Collaborate with cross-functional teams and our ML Product Manager to define the product requirements and scope of delivery of solutions to product teams.
• Work closely with our MLOps Engineer to develop and maintain pipelines for distributed training, inference optimization/quantization/serving, experiment tracking, model versioning & validation, and deployment to the cloud (AWS/Azure/GCP).
• Implement appropriate model evaluation tests, data curation processes, and apply dataset-rights awareness, and responsible AI/governance.
• Stay updated and share knowledge on the latest developments in machine learning, generative AI, natural language processing, and 3D visualization, and implement cutting-edge techniques to enhance our solutions.
• Ensure high-quality code and documentation, following best practices in software development and machine learning.

Marketing Operations

• Map, analyse, and redesign operational processes across Sales, CS, and Marketing
• Identify inefficiencies, eliminate silos, and replace manual effort with scalable automation - proactively, not just reactively
• Drive and lead cross-functional automation and process improvement initiatives end-to-end - from scoping and stakeholder alignment through to implementation and handover
• Own the configuration, architecture, and health of core go-to-market automation platforms
• Maintain strong working knowledge of Salesforce
• Design and maintain integrations across the revenue tech stack
• Own data accuracy, consistency, and integrity across platforms
• Own end-to-end testing and validation of all automation workflows before they go live
• Continuously evaluate current processes and system architectures

Machine Learning Engineer

Marketing Automation Manager